Upload ShukaPipeline

README.md

@@ -0,0 +1,199 @@
+---
+library_name: transformers
+tags: []
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]

config.json

@@ -0,0 +1,195 @@
+{
+  "_name_or_path": "runs/llama3_saaras_enhi_v0.9.4",
+  "architectures": [
+    "ShukaModel"
+  ],
+  "audio_config": {
+    "_name_or_path": "sarvam/saaras_0_11",
+    "activation_dropout": 0.0,
+    "activation_function": "gelu",
+    "apply_spec_augment": true,
+    "architectures": [
+      "WhisperForConditionalGeneration"
+    ],
+    "attention_dropout": 0.0,
+    "begin_suppress_tokens": [
+      220,
+      50257
+    ],
+    "bos_token_id": 50257,
+    "d_model": 1280,
+    "decoder_attention_heads": 20,
+    "decoder_ffn_dim": 5120,
+    "decoder_layerdrop": 0.0,
+    "decoder_layers": 32,
+    "decoder_start_token_id": 50258,
+    "dropout": 0.0,
+    "encoder_attention_heads": 20,
+    "encoder_ffn_dim": 5120,
+    "encoder_layerdrop": 0.0,
+    "encoder_layers": 32,
+    "eos_token_id": 50257,
+    "forced_decoder_ids": [
+      [
+        1,
+        50259
+      ],
+      [
+        2,
+        50359
+      ],
+      [
+        3,
+        50363
+      ]
+    ],
+    "init_std": 0.02,
+    "is_encoder_decoder": true,
+    "max_length": 448,
+    "max_source_positions": 1500,
+    "max_target_positions": 448,
+    "median_filter_width": 7,
+    "model_type": "whisper",
+    "num_hidden_layers": 32,
+    "num_mel_bins": 80,
+    "pad_token_id": 50257,
+    "scale_embedding": false,
+    "suppress_tokens": [
+      1,
+      2,
+      7,
+      8,
+      9,
+      10,
+      14,
+      25,
+      26,
+      27,
+      28,
+      29,
+      31,
+      58,
+      59,
+      60,
+      61,
+      62,
+      63,
+      90,
+      91,
+      92,
+      93,
+      359,
+      503,
+      522,
+      542,
+      873,
+      893,
+      902,
+      918,
+      922,
+      931,
+      1350,
+      1853,
+      1982,
+      2460,
+      2627,
+      3246,
+      3253,
+      3268,
+      3536,
+      3846,
+      3961,
+      4183,
+      4667,
+      6585,
+      6647,
+      7273,
+      9061,
+      9383,
+      10428,
+      10929,
+      11938,
+      12033,
+      12331,
+      12562,
+      13793,
+      14157,
+      14635,
+      15265,
+      15618,
+      16553,
+      16604,
+      18362,
+      18956,
+      20075,
+      21675,
+      22520,
+      26130,
+      26161,
+      26435,
+      28279,
+      29464,
+      31650,
+      32302,
+      32470,
+      36865,
+      42863,
+      47425,
+      49870,
+      50254,
+      50258,
+      50358,
+      50359,
+      50360,
+      50361,
+      50362
+    ],
+    "torch_dtype": "float32",
+    "use_cache": true,
+    "vocab_size": 51865
+  },
+  "audio_model_id": null,
+  "audio_token_index": 32000,
+  "auto_map": {
+    "AutoConfig": "shuka_config.ShukaConfig",
+    "AutoModel": "shuka_model.ShukaModel"
+  },
+  "custom_pipelines": {
+    "shuka-pipeline": {
+      "impl": "shuka_pipeline.ShukaPipeline",
+      "pt": [
+        "AutoModel"
+      ],
+      "tf": [],
+      "type": "multimodal"
+    }
+  },
+  "encoder_ds_factor": 160,
+  "hidden_size": 4096,
+  "ignore_index": -100,
+  "initializer_range": 0.02,
+  "model_type": "shuka",
+  "norm_init": 0.4,
+  "projector_act": "silu",
+  "stack_factor": 8,
+  "text_config": {
+    "_name_or_path": "meta-llama/Meta-Llama-3-8B-Instruct",
+    "architectures": [
+      "LlamaForCausalLM"
+    ],
+    "bos_token_id": 128000,
+    "eos_token_id": 128009,
+    "intermediate_size": 14336,
+    "max_position_embeddings": 8192,
+    "model_type": "llama",
+    "num_key_value_heads": 8,
+    "rms_norm_eps": 1e-05,
+    "rope_theta": 500000.0,
+    "torch_dtype": "bfloat16",
+    "vocab_size": 128256
+  },
+  "text_model_id": null,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.41.2",
+  "vocab_size": 128256
+}

generation_config.json

@@ -0,0 +1,7 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 128000,
+  "eos_token_id": 128009,
+  "pad_token_id": 128009,
+  "transformers_version": "4.41.2"
+}

model-00001-of-00004.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:579097641f55dab4a03be00c73fcab08ab599e82ac1bbd96ff11cd08b4e0e95b
+size 4941662064

model-00002-of-00004.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:15f03a7aa67f4aefd27c3fab1684b8a49c0636f2d572f6316371e043366b0d96
+size 4999820896

model-00003-of-00004.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2e97a7b690d34b2901edd649da811c7bf7f388e56d865dad266e91a32e515620
+size 4915917680

model-00004-of-00004.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dfbb9312a19aca5dc65ceefe16b6b64b6a408ad639e5346a2a763be8cff30d44
+size 2594255080

model.safetensors.index.json

@@ -0,0 +1,789 @@
+{
+  "metadata": {
+    "total_size": 17451560960
+  },
+  "weight_map": {
+    "audio_tower.conv1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.conv1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.conv2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.conv2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.embed_positions.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.0.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.1.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.10.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.11.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.12.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.13.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.14.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.15.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.16.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.17.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.18.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.19.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.2.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.20.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.21.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.22.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.23.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.24.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.25.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.26.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.27.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.28.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.29.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.3.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.30.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.31.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.4.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.5.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.6.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.7.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.8.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.fc1.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.fc1.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.fc2.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.fc2.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.final_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.final_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.self_attn.out_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.self_attn.out_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.self_attn.q_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.self_attn.v_proj.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.self_attn_layer_norm.bias": "model-00001-of-00004.safetensors",
+    "audio_tower.layers.9.self_attn_layer_norm.weight": "model-00001-of-00004.safetensors",
+    "language_model.lm_head.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.embed_tokens.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.0.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.0.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.0.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.0.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.0.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.0.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.0.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.0.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.0.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.1.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.1.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.1.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.1.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.1.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.1.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.1.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.1.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.1.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.10.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.10.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.10.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.10.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.10.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.10.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.10.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.10.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.10.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.11.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.11.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.11.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.11.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.11.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.11.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.11.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.11.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.11.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.12.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.12.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.12.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.12.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.12.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.12.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.12.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.12.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.12.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.13.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.13.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.13.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.13.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.13.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.13.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.13.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.13.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.13.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.14.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.14.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.14.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.14.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.14.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.14.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.14.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.14.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.14.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.15.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.15.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.15.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.15.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.15.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.15.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.15.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.15.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.15.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.16.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.16.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.16.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.16.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.16.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.16.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.16.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.16.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.16.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.17.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.17.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.17.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.17.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.17.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.17.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.17.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.17.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.17.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.18.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.18.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.18.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.18.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.18.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.18.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.18.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.18.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.18.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.19.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.19.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.19.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.19.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.19.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.19.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.19.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.19.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.19.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.2.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.2.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.2.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.2.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.2.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.2.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.2.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.2.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.2.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.20.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.20.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.20.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.20.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.20.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.20.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.20.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.20.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.20.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.21.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.21.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.21.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.21.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.21.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.21.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.21.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.21.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.21.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.22.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.22.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.22.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.22.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.22.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.22.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.22.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.22.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.22.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.23.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.23.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.23.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.23.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.23.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.23.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.23.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.23.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.23.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.24.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.24.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.24.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.24.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.24.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.24.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.24.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.24.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.24.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.25.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.25.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.25.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.25.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.25.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.25.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.25.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.25.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.25.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.26.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.26.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.26.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.26.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.26.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.26.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.26.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.26.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.26.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.27.input_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.27.mlp.down_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.27.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.27.mlp.up_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.27.post_attention_layernorm.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.27.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.27.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.27.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.27.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.28.input_layernorm.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.28.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.28.mlp.gate_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.28.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.28.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.28.self_attn.k_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.28.self_attn.o_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.28.self_attn.q_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.28.self_attn.v_proj.weight": "model-00003-of-00004.safetensors",
+    "language_model.model.layers.29.input_layernorm.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.29.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.29.mlp.gate_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.29.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.29.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.29.self_attn.k_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.29.self_attn.o_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.29.self_attn.q_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.29.self_attn.v_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.3.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.3.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.3.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.3.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.3.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.3.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.3.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.3.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.3.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.30.input_layernorm.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.30.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.30.mlp.gate_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.30.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.30.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.30.self_attn.k_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.30.self_attn.o_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.30.self_attn.q_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.30.self_attn.v_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.31.input_layernorm.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.31.mlp.down_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.31.mlp.gate_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.31.mlp.up_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.31.post_attention_layernorm.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.31.self_attn.k_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.31.self_attn.o_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.31.self_attn.q_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.31.self_attn.v_proj.weight": "model-00004-of-00004.safetensors",
+    "language_model.model.layers.4.input_layernorm.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.4.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.4.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.4.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.4.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.4.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.4.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.4.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.4.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.5.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.5.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.5.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.5.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.5.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.5.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.5.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.5.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.5.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
+    "language_model.model.layers.6.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.6.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.6.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.6.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.6.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.6.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.6.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.6.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.6.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.7.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.7.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.7.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.7.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.7.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.7.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.7.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.7.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.7.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.8.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.8.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.8.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.8.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.8.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.8.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.8.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.8.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.8.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.9.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.9.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.9.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.9.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
+    "language_model.model.norm.weight": "model-00004-of-00004.safetensors",
+    "multi_modal_projector.linear_1.weight": "model-00001-of-00004.safetensors",
+    "multi_modal_projector.linear_2.weight": "model-00001-of-00004.safetensors",
+    "multi_modal_projector.ln_post.weight": "model-00001-of-00004.safetensors",
+    "multi_modal_projector.ln_pre.weight": "model-00001-of-00004.safetensors"
+  }
+}

shuka_config.py

@@ -0,0 +1,149 @@
+####################################################################
+## Built on top of Ultravox: https://github.com/fixie-ai/ultravox ##
+####################################################################
+
+import dataclasses
+from typing import Any, Dict, List, Optional
+
+import transformers
+
+
+@dataclasses.dataclass
+class LoraConfigSimplified:
+    """
+    Low Rank Approximation (LoRA) configuration.
+
+    Used for language and audio models separately.
+    """
+
+    # The rank of the approximation
+    r: int = 0
+    lora_alpha: float = 8
+    target_modules: Optional[List[str]] = dataclasses.field(
+        default_factory=lambda: ["k_proj", "q_proj", "linear_k", "linear_q"]
+    )
+
+
+class ShukaConfig(transformers.PretrainedConfig):
+    r"""
+    This is the configuration class to store the configuration of a [`ShukaForConditionalGeneration`]. It is used to instantiate an
+    Shuka model according to the specified arguments, defining the model architecture.
+
+    Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
+    documentation from [`PretrainedConfig`] for more information.
+
+    Args:
+        audio_config (`Wav2Vec2Config`,  *optional*):
+            Custom audio config or dict
+        text_config (`Union[AutoConfig, dict]`, *optional*):
+            The config object of the text backbone. Can be any of `LlamaConfig` or `MistralConfig`.
+        ignore_index (`int`, *optional*, defaults to -100):
+            The ignore index for the loss function.
+        audio_token_index (`int`, *optional*, defaults to 32000):
+            The audio token index to encode the audio prompt.
+        encoder_ds_factor (`int`, *optional*, defaults to 320):
+            The audio encoder downsample factor.
+        stack_factor (`int`, *optional*, defaults to 8):
+            Audio downsampling factor for the multimodal projector.
+        norm_init (`float`, *optional*, defaults to 0.4):
+            The initialization value for the layer normalization.
+        projector_act (`str`, *optional*, defaults to `"silu"`):
+            The activation function used by the multimodal projector.
+        text_model_lora_config (`LoraConfigSimplified`, *optional*):
+            The LoRA configuration for finetuning the text model.
+        audio_model_lora_config (`LoraConfigSimplified`, *optional*):
+            The LoRA configuration for finetuning the audio model.
+
+
+    Example:
+
+    ```python
+    >>> from transformers import ShukaForConditionalGeneration, Wav2Vec2Config, ShukaConfig, LlamaConfig
+
+    >>> # Initializing an audio encoder config
+    >>> audio_config = Wav2Vec2Config()
+
+    >>> # Initializing a Llama config
+    >>> text_config = LlamaConfig()
+
+    >>> # Initializing a default configuration
+    >>> configuration = ShukaConfig(audio_config, text_config)
+
+    >>> # Initializing a completely untrained model from the configuration
+    >>> model = ShukaForConditionalGeneration(configuration)
+
+    >>> # Accessing the model configuration
+    >>> configuration = model.config
+
+    >>> # Initialize a model from pretrained checkpoints and random projector weights
+    >>> config = ShukaConfig(audio_model_id="facebook/wav2vec2-base-960h", text_model_id="meta-llama/Llama-2-7b-chat-hf")
+    ```"""
+
+    model_type = "shuka"
+    is_composition = False
+
+    def __init__(
+        self,
+        audio_config: Optional[Dict[str, Any]] = None,
+        text_config: Optional[Dict[str, Any]] = None,
+        audio_model_id: Optional[str] = None,
+        text_model_id: Optional[str] = None,
+        ignore_index: int = -100,
+        audio_token_index: int = 32000,
+        hidden_size: int = 4096,
+        encoder_ds_factor: int = 320,
+        stack_factor: int = 8,
+        norm_init: float = 0.4,
+        projector_act: str = "silu",
+        text_model_lora_config: Optional[LoraConfigSimplified] = None,
+        audio_model_lora_config: Optional[LoraConfigSimplified] = None,
+        **kwargs,
+    ):
+        self.ignore_index = ignore_index
+
+        self.audio_model_id = audio_model_id
+        self.text_model_id = text_model_id
+        self.audio_token_index = audio_token_index
+
+        self.hidden_size = hidden_size
+        self.encoder_ds_factor = encoder_ds_factor
+        self.stack_factor = stack_factor
+        self.norm_init = norm_init
+        self.projector_act = projector_act
+
+        if text_model_id is not None:
+            self.text_config: transformers.LlamaConfig = (
+                transformers.AutoConfig.from_pretrained(text_model_id)
+            )
+        else:
+            text_config = text_config or {}
+            self.text_config = transformers.CONFIG_MAPPING[
+                text_config.get("model_type", "llama")
+            ](**text_config)
+
+        if audio_model_id is not None:
+            self.audio_config: transformers.PretrainedConfig = (
+                transformers.AutoConfig.from_pretrained(audio_model_id)
+            )
+        else:
+            audio_config = audio_config or {}
+            self.audio_config = transformers.CONFIG_MAPPING[
+                audio_config.get("model_type", "wav2vec2")
+            ](**audio_config)
+
+        self.text_model_lora_config = (
+            text_model_lora_config
+            if isinstance(text_model_lora_config, dict)
+            else dataclasses.asdict(text_model_lora_config or LoraConfigSimplified())
+        )
+        self.audio_model_lora_config = (
+            audio_model_lora_config
+            if isinstance(audio_model_lora_config, dict)
+            else dataclasses.asdict(audio_model_lora_config or LoraConfigSimplified())
+        )
+
+        self.vocab_size = self.text_config.vocab_size
+
+        self.initializer_range = self.text_config.initializer_range
+
+        super().__init__(**kwargs)

shuka_model.py

@@ -0,0 +1,413 @@
+####################################################################
+## Built on top of Ultravox: https://github.com/fixie-ai/ultravox ##
+####################################################################
+
+import logging
+from typing import Any, Dict, Optional, Set, Tuple, Union
+
+import peft
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+import transformers
+import transformers.activations
+import transformers.modeling_outputs
+import transformers.models
+
+from .shuka_config import ShukaConfig
+from .whisper_model_modified import WhisperEncoder as ModifiedWhisperEncoder
+
+
+class ShukaModel(
+    transformers.LlamaPreTrainedModel,
+    transformers.GenerationMixin,
+):
+    """
+    The Shuka model which consists of an audio encoder and a language model.
+
+    Audio input is processed by the audio encoder, then every `stack_factor` frames are stacked together and
+    projected to the language model's embedding space using a few linear layers.
+    The text is embedded by the language model as usual and then the audio and text embeddings are merged together.
+
+    A special token `<|audio|>` is used to indicate the start of the audio embeddings in the merged embeddings.
+
+    Parameters:
+        config: Model configuration class with all the parameters of the model.
+    """
+
+    config_class = ShukaConfig
+    config: ShukaConfig  # for type hinting
+    _no_split_modules = ["Wav2Vec2Model", "WhisperEncoder", "LlamaDecoderLayer"]
+
+    def __init__(self, config: ShukaConfig):
+        super().__init__(config)
+
+        self.keep_params: Set[str] = set()
+        self.vocab_size = config.vocab_size
+
+        self.audio_tower = self._create_audio_tower(config)
+        self.multi_modal_projector = ShukaProjector(config)
+        self.language_model = self._create_language_model(config)
+
+        self.post_init()
+
+    def get_input_embeddings(self):
+        return self.language_model.get_input_embeddings()
+
+    def set_input_embeddings(self, value):
+        self.language_model.set_input_embeddings(value)
+
+    def get_output_embeddings(self):
+        return self.language_model.get_output_embeddings()
+
+    def set_output_embeddings(self, new_embeddings):
+        self.language_model.set_output_embeddings(new_embeddings)
+
+    def set_decoder(self, decoder):
+        self.language_model.set_decoder(decoder)
+
+    def get_decoder(self):
+        return self.language_model.get_decoder()
+
+    def tie_weights(self):
+        return self.language_model.tie_weights()
+
+    def _setup_cache(
+        self, cache_cls, max_batch_size: int, max_cache_len: Optional[int] = None
+    ):
+        self.language_model._setup_cache(cache_cls, max_batch_size, max_cache_len)
+
+    def _reorder_cache(self, past_key_values, beam_idx):
+        return self.language_model._reorder_cache(past_key_values, beam_idx)
+
+    def resize_token_embeddings(
+        self,
+        new_num_tokens: Optional[int] = None,
+        pad_to_multiple_of: Optional[int] = None,
+    ) -> nn.Embedding:
+        model_embeds = self.language_model.resize_token_embeddings(
+            new_num_tokens, pad_to_multiple_of
+        )
+        # update vocab size
+        self.config.text_config.vocab_size = model_embeds.num_embeddings
+        self.config.vocab_size = model_embeds.num_embeddings
+        self.vocab_size = model_embeds.num_embeddings
+        return model_embeds
+
+    def forward(
+        self,
+        input_ids: torch.Tensor,
+        audio_values: Optional[torch.Tensor] = None,
+        inputs_embeds: Optional[torch.Tensor] = None,
+        labels: Optional[torch.Tensor] = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        audio_token_start_idx: Optional[torch.Tensor] = None,
+        audio_token_len: Optional[torch.Tensor] = None,
+        past_key_values: Optional[Tuple] = None,
+        **kwargs,
+    ) -> Union[Tuple, transformers.modeling_outputs.CausalLMOutputWithPast]:
+        """
+        Forward pass for the Shuka model.
+
+        `input_ids` are the tokenized text input. They are embedded by the language model as usual.
+        `audio_values` are processed by the audio encoder and then every `stack_factor` frames are stacked together and
+        projected to the language model's embedding space using a few linear layers.
+        The audio and text embeddings are merged together. A special token `<|audio|>` is used to indicate the start
+        of the audio embeddings in the merged embeddings.
+
+        Args:
+            input_ids: The tokenized text input.
+            audio_values: The processed audio values.
+            inputs_embeds: The embeddings for the input tokens.
+            labels: The tokenized text labels.
+            attention_mask: The attention mask for the input.
+            position_ids: The position ids for the input.
+            past_key_values: The past key value cache for the language model attention layers.
+            **kwargs: Additional keyword arguments. Passed directly to the language model.
+        """
+        if inputs_embeds is None:
+            # B x T  ->  B x T x D
+            inputs_embeds = self.get_input_embeddings().forward(input_ids)
+
+        if audio_values is not None:
+            assert (
+                audio_token_start_idx is not None and audio_token_len is not None
+            ), "audio_token_start_idx and audio_token_len must be provided if audio_values are provided."
+            assert (
+                len(audio_token_start_idx) == len(audio_token_len) == len(audio_values)
+            ), "audio_token_start_idx, audio_token_len, and audio_values must have the same batch size."
+
+            audio_values = audio_values.to(inputs_embeds.dtype)
+            # B x A/3200 x D
+            audio_tower_output = self.audio_tower.forward(
+                audio_values
+            ).last_hidden_state
+
+            audio_embeds = self.multi_modal_projector.forward(audio_tower_output)
+
+            # combine audio and text embeddings
+            for i, (audio, start, length) in enumerate(
+                zip(audio_embeds, audio_token_start_idx, audio_token_len)
+            ):
+                length = min(length, audio.shape[0])
+                inputs_embeds[i, start : start + length] = audio[:length]
+
+        lm_output = self.language_model.forward(
+            inputs_embeds=inputs_embeds,
+            labels=labels,
+            attention_mask=attention_mask,
+            past_key_values=past_key_values,
+            **kwargs,
+        )
+
+        return lm_output
+
+    def prepare_inputs_for_generation(
+        self,
+        input_ids: torch.Tensor,
+        audio_values: Optional[torch.FloatTensor] = None,
+        audio_token_start_idx: Optional[torch.Tensor] = None,
+        audio_token_len: Optional[torch.Tensor] = None,
+        past_key_values: Optional[Tuple] = None,
+        attention_mask: Optional[torch.Tensor] = None,
+        inputs_embeds: Optional[torch.Tensor] = None,
+        **kwargs,
+    ) -> Dict[str, Any]:
+        model_input = self.language_model.prepare_inputs_for_generation(
+            input_ids=input_ids,
+            past_key_values=past_key_values,
+            attention_mask=attention_mask,
+            inputs_embeds=inputs_embeds,
+            **kwargs,
+        )
+
+        if past_key_values is None and audio_values is not None:
+            # We only want to use audio features in the 1st generation step
+            model_input["audio_values"] = audio_values
+            model_input["audio_token_start_idx"] = audio_token_start_idx
+            model_input["audio_token_len"] = audio_token_len
+
+        return model_input
+
+    @classmethod
+    def _create_audio_tower(cls, config: ShukaConfig) -> Union[
+        transformers.Wav2Vec2Model,
+        transformers.models.whisper.modeling_whisper.WhisperEncoder,
+    ]:
+        if config.audio_model_id is not None:
+            if (
+                "whisper" in config.audio_model_id is not None
+                or "saaras" in config.audio_model_id is not None
+            ):
+                audio_tower = ModifiedWhisperEncoder.from_pretrained(
+                    config.audio_model_id
+                )
+            else:
+                audio_tower = transformers.AutoModel.from_pretrained(
+                    config.audio_model_id
+                )
+        else:
+            if (
+                "whisper" in config.audio_config._name_or_path
+                or "saaras" in config.audio_config._name_or_path
+            ):
+                audio_tower = ModifiedWhisperEncoder(config.audio_config)
+            else:
+                audio_tower = transformers.AutoModel.from_config(config.audio_config)
+
+        if isinstance(
+            audio_tower,
+            (transformers.Wav2Vec2BertModel, transformers.WhisperModel),
+        ):
+            # For these models we only need the encoder part
+            # Wav2Vec2BertModel -> Wav2Vec2BertEncoder
+            # WhisperModel -> WhisperEncoder
+            audio_tower = audio_tower.encoder
+
+        audio_tower = apply_lora(audio_tower, config.audio_model_lora_config)
+        return audio_tower
+
+    @classmethod
+    def _create_language_model(
+        cls, config: ShukaConfig
+    ) -> transformers.LlamaForCausalLM:
+        if config.text_model_id is not None:
+            language_model = transformers.AutoModelForCausalLM.from_pretrained(
+                config.text_model_id, attn_implementation=config._attn_implementation
+            )
+        else:
+            language_model = transformers.AutoModelForCausalLM.from_config(
+                config.text_config, attn_implementation=config._attn_implementation
+            )
+
+        language_model = apply_lora(language_model, config.text_model_lora_config)
+        return language_model
+
+    def merge_and_unload(self):
+        if isinstance(self.language_model, peft.PeftModel):
+            self.language_model = self.language_model.merge_and_unload()
+        if isinstance(self.audio_tower, peft.PeftModel):
+            self.audio_tower = self.audio_tower.merge_and_unload()
+
+        self.config.text_model_id = None
+        self.keep_params.update(
+            set(
+                [
+                    f"language_model.{name}"
+                    for name, _ in self.language_model.named_parameters()
+                ]
+            )
+        )
+        self.config.audio_model_id = None
+        self.keep_params.update(
+            set(
+                [
+                    f"audio_tower.{name}"
+                    for name, _ in self.audio_tower.named_parameters()
+                ]
+            )
+        )
+        for param in ["text_model_lora_config", "audio_model_lora_config"]:
+            if hasattr(self.config, param):
+                delattr(self.config, param)
+
+    def push_to_hub(self, *args, **kwargs):
+        self.merge_and_unload()
+        self.to(self.language_model.dtype)
+        return super().push_to_hub(*args, **kwargs)
+
+    def state_dict(self, *args, **kwargs):
+        named_params = dict(self.named_parameters())
+        state_dict = super().state_dict(*args, **kwargs)
+
+        state_dict = {
+            k: v
+            for k, v in state_dict.items()
+            if k in self.keep_params
+            or (k in named_params and named_params[k].requires_grad)
+        }
+        return state_dict
+
+    def load_state_dict(
+        self,
+        state_dict: Dict[str, Any],
+        *args,
+        **kwargs,
+    ):
+        self.keep_params.update(set(state_dict.keys()))
+        return super().load_state_dict(state_dict, *args, **kwargs)
+
+    def print_trainable_parameters(self):
+        """
+        Prints the number of trainable parameters in the model (reuses Peft model's method)
+        """
+        count_params = peft.peft_model.PeftModel.get_nb_trainable_parameters
+
+        trainable_params, all_param = count_params(self)
+
+        logging.info(
+            f"trainable params: {trainable_params:,d} || all params: {all_param:,d}"
+            f" || trainable%: {100 * trainable_params / all_param:.1f}%"
+        )
+
+        lm_trainable_params, lm_all_params = count_params(self.language_model)
+        audio_trainable_params, audio_all_params = count_params(self.audio_tower)
+
+        projector_trainable_params = (
+            trainable_params - lm_trainable_params - audio_trainable_params
+        )
+        projector_all_params = all_param - lm_all_params - audio_all_params
+
+        logging.info(
+            f"Trainable%:   "
+            f" LLM: {100 * lm_trainable_params / lm_all_params:.1f}%"
+            f" || Audio Encoder: {100 * audio_trainable_params / audio_all_params:.1f}%"
+            f" || Projector: {100 * projector_trainable_params / projector_all_params:.1f}%"
+        )
+
+
+def apply_lora(model: torch.nn.Module, lora_config: dict) -> torch.nn.Module:
+    """
+    Applies LoRA finetuning to the model. If the `r` parameter is set to 0, the model is frozen instead.
+    """
+    lora_config = peft.LoraConfig(**lora_config or {})
+
+    if lora_config.r == 0:
+        # freeze the model entirely
+        for param in model.parameters():
+            param.requires_grad = False
+    else:
+        model = peft.get_peft_model(model, lora_config)
+
+    return model
+
+
+class StackAudioFrames(nn.Module):
+    """
+    Stack the audio embedding frames to reduce the sequence length by a factor of `stack_factor`.
+
+    The number of output frames will be `ceil(T / stack_factor) + 1` where `T` is the number of input frames.
+    NOTE: the extra +1 is intentional: in case the number of audio tokens are over-estimated by the processor,
+    we want to make sure `processor.audio_token_replacement` (i.e. EOS) doesn't get leaked into the middle of embeddings.
+    In most cases this extra padding will get removed in the model's forward function so it has no effect.
+    """
+
+    def __init__(self, stack_factor: int = 8):
+        super().__init__()
+        self.stack_factor = stack_factor
+
+    def forward(self, audio_embeds: torch.Tensor) -> torch.Tensor:
+        B, T, C = audio_embeds.shape
+        T_pad = (T + self.stack_factor - 1) // self.stack_factor * self.stack_factor
+        audio_embeds = F.pad(audio_embeds, (0, 0, 0, T_pad - T + self.stack_factor))
+        B, T, C = audio_embeds.shape
+        audio_embeds = audio_embeds.view(
+            B, T // self.stack_factor, C * self.stack_factor
+        )
+        return audio_embeds
+
+
+class RMSNorm(transformers.models.llama.modeling_llama.LlamaRMSNorm):
+    def __init__(self, hidden_size: int, init: float = 1, eps: float = 1e-6):
+        super().__init__(hidden_size=hidden_size, eps=eps)
+        self.weight.data.fill_(init)
+
+
+class SwiGLU(nn.Module):
+    def forward(self, x):
+        x, gate = x.chunk(2, dim=-1)
+        return F.silu(gate) * x
+
+
+class ShukaProjector(nn.Sequential):
+    def __init__(self, config: ShukaConfig):
+        super().__init__()
+        self.hidden_dim = config.hidden_size
+        self._pad_and_stack = StackAudioFrames(config.stack_factor)
+        dim = config.audio_config.hidden_size * config.stack_factor
+        self.ln_pre = RMSNorm(dim, init=config.norm_init)
+        self.linear_1 = nn.Linear(dim, self.hidden_dim, bias=False)
+        dim = self.hidden_dim
+        self.act = transformers.activations.get_activation(config.projector_act)
+        dim = dim // 2 if config.projector_act == "swiglu" else dim
+        self.linear_2 = nn.Linear(dim, config.text_config.hidden_size, bias=False)
+        self.ln_post = RMSNorm(config.text_config.hidden_size, init=config.norm_init)
+
+    def forward(self, audio_features: torch.Tensor) -> torch.Tensor:
+        audio_features = self._pad_and_stack(audio_features)
+        audio_features = self.ln_pre(audio_features)
+        hidden_states = self.linear_1(audio_features)
+        hidden_states = self.act(hidden_states)
+        hidden_states = self.linear_2(hidden_states)
+        hidden_states = self.ln_post(hidden_states)
+        return hidden_states
+
+
+ShukaConfig.register_for_auto_class()
+ShukaModel.register_for_auto_class()
+
+transformers.AutoConfig.register("shuka", ShukaConfig)
+transformers.AutoModel.register(ShukaConfig, ShukaModel)
+
+transformers.activations.ACT2FN["swiglu"] = SwiGLU
+transformers.activations.ACT2FN["swiglu"] = SwiGLU

shuka_pipeline.py

@@ -0,0 +1,131 @@
+####################################################################
+## Built on top of Ultravox: https://github.com/fixie-ai/ultravox ##
+####################################################################
+
+import logging
+from typing import Any, Dict, List, Optional
+
+import numpy as np
+import transformers
+
+# We must use relative import in this directory to allow uploading to HF Hub
+# Even "from . import X" pattern doesn't work (undocumented and unclear why)
+from .shuka_model import ShukaModel
+from .shuka_processing import ShukaProcessor
+
+
+class ShukaPipeline(transformers.Pipeline):
+    def __init__(
+        self,
+        model: ShukaModel,
+        tokenizer: Optional[transformers.PreTrainedTokenizerBase] = None,
+        audio_processor: Optional[transformers.ProcessorMixin] = None,
+        **kwargs
+    ):
+        if tokenizer is None:
+            try:
+                tokenizer = transformers.AutoTokenizer.from_pretrained(
+                    model.config._name_or_path
+                )
+            except:
+                tokenizer = transformers.AutoTokenizer.from_pretrained(
+                    model.config.text_model_id or model.config.text_config._name_or_path
+                )
+
+        if audio_processor is None:
+            audio_processor = transformers.AutoProcessor.from_pretrained(
+                model.config.audio_model_id or model.config.audio_config._name_or_path
+            )
+
+        self.processor = ShukaProcessor(
+            audio_processor=audio_processor,
+            tokenizer=tokenizer,
+            stack_factor=model.config.stack_factor,
+        )
+
+        super().__init__(model=model, tokenizer=tokenizer, **kwargs)
+
+    def _sanitize_parameters(self, **kwargs):
+        generation_keys = ["temperature", "max_new_tokens", "repetition_penalty"]
+        generation_kwargs = {k: kwargs[k] for k in kwargs if k in generation_keys}
+        return {}, generation_kwargs, {}
+
+    def preprocess(self, inputs: Dict[str, Any]):
+        turns: list = inputs.get("turns", [])
+
+        audio = inputs.get("audio", None)
+        # Convert to float32 if needed.
+        if isinstance(audio, np.ndarray):
+            if audio.dtype == np.float64:
+                audio = audio.astype(np.float32)
+            elif audio.dtype == np.int16:
+                audio = audio.astype(np.float32) / np.float32(32768.0)
+            elif audio.dtype == np.int32:
+                audio = audio.astype(np.float32) / np.float32(2147483648.0)
+
+        if audio is not None and (len(turns) == 0 or turns[-1]["role"] != "user"):
+            prompt = inputs.get("prompt", "<|audio|>")
+            if "<|audio|>" not in prompt:
+                logging.warning(
+                    "Prompt does not contain '<|audio|>', appending '<|audio|>' to the end of the prompt."
+                )
+
+                prompt += " <|audio|>"
+            turns.append({"role": "user", "content": prompt})
+
+        text = self.processor.tokenizer.apply_chat_template(
+            turns, add_generation_prompt=True, tokenize=False
+        )
+
+        if "sampling_rate" not in inputs and audio is not None:
+            logging.warning(
+                "No sampling rate provided, using default of 16kHz. We highly recommend providing the correct sampling rate."
+            )
+
+        output = self.processor(
+            text=text,
+            audio=audio,
+            sampling_rate=inputs.get("sampling_rate", 16000),
+        )
+        if "audio_values" in output:
+            output["audio_values"] = output["audio_values"].to(self.model.dtype)
+
+        return output
+
+    def _forward(
+        self,
+        model_inputs: Dict[str, Any],
+        temperature: Optional[float] = None,
+        max_new_tokens: Optional[int] = None,
+        repetition_penalty: float = 1.1,
+    ) -> List[int]:
+        temperature = temperature or None
+        do_sample = temperature is not None
+
+        terminators = [self.tokenizer.eos_token_id]
+        if "<|eot_id|>" in self.tokenizer.added_tokens_encoder:
+            terminators.append(self.tokenizer.convert_tokens_to_ids("<|eot_id|>"))
+
+        input_len = model_inputs["input_ids"].shape[1]
+
+        outputs = self.model.generate(
+            **model_inputs,
+            do_sample=do_sample,
+            temperature=temperature,
+            max_new_tokens=max_new_tokens,
+            repetition_penalty=repetition_penalty,
+            eos_token_id=terminators
+        )
+        return outputs[0][input_len:]
+
+    def postprocess(self, model_outputs) -> str:
+        output_text = self.tokenizer.decode(model_outputs, skip_special_tokens=True)
+        return output_text
+
+
+transformers.pipelines.PIPELINE_REGISTRY.register_pipeline(
+    "shuka-pipeline",
+    pipeline_class=ShukaPipeline,
+    pt_model=transformers.AutoModel,
+    type="multimodal",
+)

shuka_processing.py

@@ -0,0 +1,176 @@
+####################################################################
+## Built on top of Ultravox: https://github.com/fixie-ai/ultravox ##
+####################################################################
+
+from typing import Optional, Union
+
+import numpy as np
+import torch
+import transformers
+
+
+class ShukaProcessor(transformers.ProcessorMixin):
+    """
+    Constructs an Shuka processor which wraps an audio processor and a tokenizer into a single processor.
+
+    Args:
+        audio_processor: The audio processor for the audio encoder.
+        tokenizer: The tokenizer for the language model.
+    """
+
+    attributes = ["audio_processor", "tokenizer"]
+    audio_processor_class = (
+        "Wav2Vec2Processor",
+        "SeamlessM4TFeatureExtractor",
+        "WhisperProcessor",
+    )
+    tokenizer_class = (
+        "PreTrainedTokenizer",
+        "PreTrainedTokenizerFast",
+    )
+
+    tokenizer: transformers.PreTrainedTokenizerBase
+    audio_processor: transformers.ProcessorMixin
+
+    def __init__(
+        self,
+        audio_processor=None,
+        tokenizer=None,
+        audio_padding: str = "longest",
+        encoder_ds_factor: int = 320,
+        stack_factor: int = 8,
+        audio_placeholder: str = "<|audio|>",
+    ):
+        """
+        Args:
+            audio_processor: The audio processor for the audio encoder.
+            tokenizer: The tokenizer for the language model.
+            audio_padding: The padding strategy for the audio encoder.
+            encoder_ds_factor: The downsample factor of the audio encoder.
+            stack_factor: The factor by which the audio encoder output is stacked in the multimodal projector.
+            audio_placeholder: The placeholder for the audio in the text.
+        """
+        self.audio_padding = audio_padding
+        self.encoder_ds_factor = encoder_ds_factor
+        self.stack_factor = stack_factor
+        self.audio_placeholder = audio_placeholder
+        self.audio_token_replacement = tokenizer.eos_token
+        assert (
+            self.audio_token_replacement is not None
+        ), "The tokenizer has no EOS token. Cannot recover."
+        super().__init__(audio_processor=audio_processor, tokenizer=tokenizer)
+
+    def __call__(
+        self,
+        text: Optional[str] = None,
+        audio: Optional[Union[np.ndarray, torch.Tensor]] = None,
+        sampling_rate: Optional[int] = None,
+        return_tensors: Optional[
+            Union[str, transformers.TensorType]
+        ] = transformers.TensorType.PYTORCH,
+        **kwargs,
+    ) -> transformers.BatchFeature:
+        """
+        Main method to prepare for the model one text sequence and audio. This method forwards the `text`
+        and `kwargs` arguments to PreTrainedTokenizerFast's [`~PreTrainedTokenizerFast.__call__`] if `text` is not `None` to encode
+        the text. To prepare the audio(s), this method forwards the `audio`, `sampling_rate` and `kwargs` arguments to
+        audio processor's [`~Wav2Vec2Processor.__call__`] if `audio` is not `None`. Please refer to the docstring
+        of the above two methods for more information.
+
+        Args:
+            text (`str`, `List[str]`):
+                The sequence to be encoded. Sequence can be a string or (pretokenized string).
+            audio (`np.ndarray`, `torch.Tensor`, `List[np.ndarray]`, `List[torch.Tensor]`):
+                The audio to be prepared. Audio can be NumPy array or PyTorch tensor. In case of a
+                NumPy array/PyTorch tensor, each audio should be of shape (C, T), where C is a number of channels, and T the
+                sample length of the audio.
+            sampling_rate (`int`, *optional*, defaults to 16000):
+                Sampling rate of the input audio. We expect 16kHz audio. Don't change this value unless you know what
+                you are doing.
+            return_tensors (`str` or [`~utils.TensorType`], *optional*):
+                If set, will return tensors of a particular framework. Acceptable values are:
+
+                - `'tf'`: Return TensorFlow `tf.constant` objects.
+                - `'pt'`: Return PyTorch `torch.Tensor` objects.
+                - `'np'`: Return NumPy `np.ndarray` objects.
+                - `'jax'`: Return JAX `jnp.ndarray` objects.
+
+        Returns:
+            [`BatchFeature`]: A [`BatchFeature`] with the following fields:
+
+            - **input_ids** -- List of token ids to be fed to a model. Returned when `text` is not `None`.
+            - **attention_mask** -- List of indices specifying which tokens should be attended to by the model (when
+              `return_attention_mask=True` or if *"attention_mask"* is in `self.model_input_names` and if `text` is not
+              `None`).
+            - **audio_values** -- Processed audio values to be fed to a model. Returned when `audio` is not `None`.
+            - **audio_token_len** -- Predicted number of audio frames: this value is guaranteed to be a close upper bound.
+              Returned when `audio` is not `None`.
+            - **audio_token_start_idx** -- The index in the tokenized text where the audio starts. Returned when `audio` is not `None`.
+        """
+        # TODO: Add support for multiple audio and text inputs.
+        data = {}
+        audio_embed_frames = 0
+        if audio is not None and len(audio) > 0:
+            if self.audio_padding == "max_length":
+                # 30 seconds is the expected length for Whisper
+                assert sampling_rate is not None, "Sampling rate must be provided."
+                audio_len = 30 * sampling_rate
+            else:
+                audio_len = audio.shape[-1]
+            # It's guaranteed that the number of frames is less than or equal to this amount.
+            # For Whisper this is exact AFAICT, but for Wav2Vec2 it's an upper bound.
+            # Currently, StackAudioFrames makes sure an over-estimation won't cause issues by padding the audio embeddings.
+            nb_encoder_frames = int(round(audio_len / self.encoder_ds_factor + 1e-4))
+            audio_embed_frames = int(np.ceil(nb_encoder_frames / self.stack_factor))
+            data["audio_token_len"] = [audio_embed_frames]
+
+            x = self.audio_processor(
+                audio,
+                sampling_rate=sampling_rate,
+                padding="longest",
+                max_length=audio_len,
+                **kwargs,
+            )
+            if "input_features" in x:
+                data["audio_values"] = x.input_features
+            else:
+                data["audio_values"] = x.input_values
+
+        if text is not None:
+            assert isinstance(
+                text, str
+            ), "Text must be a string. Batch mode not supported yet."
+            if self.audio_placeholder in text:
+                if "audio_token_len" not in data:
+                    raise ValueError(
+                        f"audio must be provided when using audio placeholder ({self.audio_placeholder}) in text."
+                    )
+
+                start_idx = len(
+                    self.tokenizer.encode(
+                        text[: text.index(self.audio_placeholder)],
+                        add_special_tokens=False,
+                    )
+                )
+                data["audio_token_start_idx"] = [start_idx]
+                text = text.replace(
+                    self.audio_placeholder,
+                    self.audio_token_replacement * audio_embed_frames,
+                )
+
+            # Special tokens like BOS should already have been added by the caller.
+            data.update(self.tokenizer([text], add_special_tokens=False, **kwargs))
+
+        return transformers.BatchFeature(data=data, tensor_type=return_tensors)
+
+    def batch_decode(self, *args, **kwargs):
+        return self.tokenizer.batch_decode(*args, **kwargs)
+
+    def decode(self, *args, **kwargs):
+        return self.tokenizer.decode(*args, **kwargs)
+
+    @property
+    def model_input_names(self):
+        tokenizer_input_names = self.tokenizer.model_input_names
+        audio_processor_input_names = self.audio_processor.model_input_names
+        return list(set(tokenizer_input_names + audio_processor_input_names))

special_tokens_map.json

@@ -0,0 +1,17 @@
+{
+  "bos_token": {
+    "content": "<|begin_of_text|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "<|eot_id|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<|eot_id|>"
+}

tokenizer_config.json

@@ -0,0 +1,2063 @@
+{
+  "added_tokens_decoder": {
+    "128000": {
+      "content": "<|begin_of_text|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128001": {
+      "content": "<|end_of_text|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128002": {
+      "content": "<|reserved_special_token_0|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128003": {
+      "content": "<|reserved_special_token_1|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128004": {
+      "content": "<|reserved_special_token_2|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128005": {
+      "content": "<|reserved_special_token_3|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128006": {
+      "content": "<|start_header_id|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128007": {
+      "content": "<|end_header_id|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128008": {
+      "content": "<|reserved_special_token_4|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128009": {
+      "content": "<|eot_id|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128010": {
+      "content": "<|reserved_special_token_5|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128011": {
+      "content": "<|reserved_special_token_6|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128012": {
+      "content": "<|reserved_special_token_7|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128013": {
+      "content": "<|reserved_special_token_8|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128014": {
+      "content": "<|reserved_special_token_9|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128015": {
+      "content": "<|reserved_special_token_10|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128016": {
+      "content": "<|reserved_special_token_11|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128017": {
+      "content": "<|reserved_special_token_12|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128018": {
+      "content": "<|reserved_special_token_13|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128019": {
+      "content": "<|reserved_special_token_14|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128020": {
+      "content": "<|reserved_special_token_15|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128021": {
+      "content": "<|reserved_special_token_16|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128022": {
+      "content": "<|reserved_special_token_17|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128023": {
+      "content": "<|reserved_special_token_18|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128024": {
+      "content": "<|reserved_special_token_19|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128025": {
+      "content": "<|reserved_special_token_20|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128026": {
+      "content": "<|reserved_special_token_21|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128027": {
+      "content": "<|reserved_special_token_22|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128028": {
+      "content": "<|reserved_special_token_23|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128029": {
+      "content": "<|reserved_special_token_24|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128030": {
+      "content": "<|reserved_special_token_25|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128031": {
+      "content": "<|reserved_special_token_26|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128032": {
+      "content": "<|reserved_special_token_27|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128033": {
+      "content": "<|reserved_special_token_28|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128034": {
+      "content": "<|reserved_special_token_29|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128035": {
+      "content": "<|reserved_special_token_30|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128036": {
+      "content": "<|reserved_special_token_31|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128037": {
+      "content": "<|reserved_special_token_32|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128038": {
+      "content": "<|reserved_special_token_33|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128039": {
+      "content": "<|reserved_special_token_34|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128040": {
+      "content": "<|reserved_special_token_35|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128041": {
+      "content": "<|reserved_special_token_36|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128042": {
+      "content": "<|reserved_special_token_37|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128043": {
+      "content": "<|reserved_special_token_38|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128044": {
+      "content": "<|reserved_special_token_39|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128045": {
+      "content": "<|reserved_special_token_40|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128046": {
+      "content": "<|reserved_special_token_41|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128047": {
+      "content": "<|reserved_special_token_42|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128048": {
+      "content": "<|reserved_special_token_43|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128049": {
+      "content": "<|reserved_special_token_44|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128050": {
+      "content": "<|reserved_special_token_45|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128051": {
+      "content": "<|reserved_special_token_46|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128052": {
+      "content": "<|reserved_special_token_47|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128053": {
+      "content": "<|reserved_special_token_48|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128054": {
+      "content": "<|reserved_special_token_49|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128055": {
+      "content": "<|reserved_special_token_50|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128056": {
+      "content": "<|reserved_special_token_51|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128057": {
+      "content": "<|reserved_special_token_52|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128058": {
+      "content": "<|reserved_special_token_53|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128059": {
+      "content": "<|reserved_special_token_54|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128060": {
+      "content": "<|reserved_special_token_55|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128061": {
+      "content": "<|reserved_special_token_56|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128062": {
+      "content": "<|reserved_special_token_57|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128063": {
+      "content": "<|reserved_special_token_58|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128064": {
+      "content": "<|reserved_special_token_59|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128065": {
+      "content": "<|reserved_special_token_60|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128066": {
+      "content": "<|reserved_special_token_61|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128067": {
+      "content": "<|reserved_special_token_62|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128068": {
+      "content": "<|reserved_special_token_63|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128069": {
+      "content": "<|reserved_special_token_64|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128070": {
+      "content": "<|reserved_special_token_65|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128071": {
+      "content": "<|reserved_special_token_66|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128072": {
+      "content": "<|reserved_special_token_67|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128073": {
+      "content": "<|reserved_special_token_68|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128074": {
+      "content": "<|reserved_special_token_69|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128075": {
+      "content": "<|reserved_special_token_70|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128076": {
+      "content": "<|reserved_special_token_71|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128077": {
+      "content": "<|reserved_special_token_72|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128078": {
+      "content": "<|reserved_special_token_73|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128079": {
+      "content": "<|reserved_special_token_74|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128080": {
+      "content": "<|reserved_special_token_75|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128081": {
+      "content": "<|reserved_special_token_76|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128082": {
+      "content": "<|reserved_special_token_77|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128083": {
+      "content": "<|reserved_special_token_78|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128084": {
+      "content": "<|reserved_special_token_79|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128085": {
+      "content": "<|reserved_special_token_80|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128086": {
+      "content": "<|reserved_special_token_81|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128087": {
+      "content": "<|reserved_special_token_82|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128088": {
+      "content": "<|reserved_special_token_83|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128089": {
+      "content": "<|reserved_special_token_84|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128090": {
+      "content": "<|reserved_special_token_85|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128091": {
+      "content": "<|reserved_special_token_86|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128092": {
+      "content": "<|reserved_special_token_87|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128093": {
+      "content": "<|reserved_special_token_88|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128094": {
+      "content": "<|reserved_special_token_89|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128095": {
+      "content": "<|reserved_special_token_90|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128096": {
+      "content": "<|reserved_special_token_91|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128097": {
+      "content": "<|reserved_special_token_92|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128098": {
+      "content": "<|reserved_special_token_93|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128099": {
+      "content": "<|reserved_special_token_94|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128100": {
+      "content": "<|reserved_special_token_95|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128101": {
+      "content": "<|reserved_special_token_96|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128102": {
+      "content": "<|reserved_special_token_97|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128103": {
+      "content": "<|reserved_special_token_98|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128104": {
+      "content": "<|reserved_special_token_99|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128105": {
+      "content": "<|reserved_special_token_100|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128106": {
+      "content": "<|reserved_special_token_101|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128107": {
+      "content": "<|reserved_special_token_102|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128108": {
+      "content": "<|reserved_special_token_103|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128109": {
+      "content": "<|reserved_special_token_104|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128110": {
+      "content": "<|reserved_special_token_105|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128111": {
+      "content": "<|reserved_special_token_106|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128112": {
+      "content": "<|reserved_special_token_107|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128113": {
+      "content": "<|reserved_special_token_108|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128114": {
+      "content": "<|reserved_special_token_109|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128115": {
+      "content": "<|reserved_special_token_110|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128116": {
+      "content": "<|reserved_special_token_111|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128117": {
+      "content": "<|reserved_special_token_112|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128118": {
+      "content": "<|reserved_special_token_113|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128119": {
+      "content": "<|reserved_special_token_114|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128120": {
+      "content": "<|reserved_special_token_115|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128121": {
+      "content": "<|reserved_special_token_116|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128122": {
+      "content": "<|reserved_special_token_117|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128123": {
+      "content": "<|reserved_special_token_118|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128124": {
+      "content": "<|reserved_special_token_119|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128125": {
+      "content": "<|reserved_special_token_120|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128126": {
+      "content": "<|reserved_special_token_121|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128127": {
+      "content": "<|reserved_special_token_122|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128128": {
+      "content": "<|reserved_special_token_123|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128129": {
+      "content": "<|reserved_special_token_124|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128130": {
+      "content": "<|reserved_special_token_125|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128131": {
+      "content": "<|reserved_special_token_126|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128132": {
+      "content": "<|reserved_special_token_127|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128133": {
+      "content": "<|reserved_special_token_128|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128134": {
+      "content": "<|reserved_special_token_129|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128135": {
+      "content": "<|reserved_special_token_130|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128136": {
+      "content": "<|reserved_special_token_131|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128137": {
+      "content": "<|reserved_special_token_132|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128138": {
+      "content": "<|reserved_special_token_133|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128139": {
+      "content": "<|reserved_special_token_134|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128140": {
+      "content": "<|reserved_special_token_135|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128141": {
+      "content": "<|reserved_special_token_136|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128142": {
+      "content": "<|reserved_special_token_137|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128143": {
+      "content": "<|reserved_special_token_138|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128144": {
+      "content": "<|reserved_special_token_139|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128145": {
+      "content": "<|reserved_special_token_140|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128146": {
+      "content": "<|reserved_special_token_141|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128147": {
+      "content": "<|reserved_special_token_142|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128148": {
+      "content": "<|reserved_special_token_143|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128149": {
+      "content": "<|reserved_special_token_144|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128150": {
+      "content": "<|reserved_special_token_145|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128151": {
+      "content": "<|reserved_special_token_146|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128152": {
+      "content": "<|reserved_special_token_147|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128153": {
+      "content": "<|reserved_special_token_148|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128154": {
+      "content": "<|reserved_special_token_149|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128155": {
+      "content": "<|reserved_special_token_150|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128156": {
+      "content": "<|reserved_special_token_151|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128157": {
+      "content": "<|reserved_special_token_152|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128158": {
+      "content": "<|reserved_special_token_153|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128159": {
+      "content": "<|reserved_special_token_154|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128160": {
+      "content": "<|reserved_special_token_155|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128161": {
+      "content": "<|reserved_special_token_156|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128162": {
+      "content": "<|reserved_special_token_157|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128163": {
+      "content": "<|reserved_special_token_158|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128164": {
+      "content": "<|reserved_special_token_159|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128165": {
+      "content": "<|reserved_special_token_160|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128166": {
+      "content": "<|reserved_special_token_161|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128167": {
+      "content": "<|reserved_special_token_162|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128168": {
+      "content": "<|reserved_special_token_163|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128169": {
+      "content": "<|reserved_special_token_164|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128170": {
+      "content": "<|reserved_special_token_165|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128171": {
+      "content": "<|reserved_special_token_166|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128172": {
+      "content": "<|reserved_special_token_167|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128173": {
+      "content": "<|reserved_special_token_168|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128174": {
+      "content": "<|reserved_special_token_169|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128175": {
+      "content": "<|reserved_special_token_170|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128176": {
+      "content": "<|reserved_special_token_171|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128177": {
+      "content": "<|reserved_special_token_172|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128178": {
+      "content": "<|reserved_special_token_173|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128179": {
+      "content": "<|reserved_special_token_174|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128180": {
+      "content": "<|reserved_special_token_175|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128181": {
+      "content": "<|reserved_special_token_176|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128182": {
+      "content": "<|reserved_special_token_177|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128183": {
+      "content": "<|reserved_special_token_178|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128184": {
+      "content": "<|reserved_special_token_179|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128185": {
+      "content": "<|reserved_special_token_180|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128186": {
+      "content": "<|reserved_special_token_181|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128187": {
+      "content": "<|reserved_special_token_182|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128188": {
+      "content": "<|reserved_special_token_183|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128189": {
+      "content": "<|reserved_special_token_184|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128190": {
+      "content": "<|reserved_special_token_185|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128191": {
+      "content": "<|reserved_special_token_186|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128192": {
+      "content": "<|reserved_special_token_187|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128193": {
+      "content": "<|reserved_special_token_188|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128194": {
+      "content": "<|reserved_special_token_189|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128195": {
+      "content": "<|reserved_special_token_190|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128196": {
+      "content": "<|reserved_special_token_191|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128197": {
+      "content": "<|reserved_special_token_192|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128198": {
+      "content": "<|reserved_special_token_193|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128199": {
+      "content": "<|reserved_special_token_194|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128200": {
+      "content": "<|reserved_special_token_195|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128201": {
+      "content": "<|reserved_special_token_196|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128202": {
+      "content": "<|reserved_special_token_197|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128203": {
+      "content": "<|reserved_special_token_198|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128204": {
+      "content": "<|reserved_special_token_199|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128205": {
+      "content": "<|reserved_special_token_200|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128206": {
+      "content": "<|reserved_special_token_201|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128207": {
+      "content": "<|reserved_special_token_202|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128208": {
+      "content": "<|reserved_special_token_203|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128209": {
+      "content": "<|reserved_special_token_204|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128210": {
+      "content": "<|reserved_special_token_205|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128211": {
+      "content": "<|reserved_special_token_206|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128212": {
+      "content": "<|reserved_special_token_207|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128213": {
+      "content": "<|reserved_special_token_208|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128214": {
+      "content": "<|reserved_special_token_209|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128215": {
+      "content": "<|reserved_special_token_210|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128216": {
+      "content": "<|reserved_special_token_211|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128217": {
+      "content": "<|reserved_special_token_212|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128218": {
+      "content": "<|reserved_special_token_213|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128219": {
+      "content": "<|reserved_special_token_214|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128220": {
+      "content": "<|reserved_special_token_215|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128221": {
+      "content": "<|reserved_special_token_216|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128222": {
+      "content": "<|reserved_special_token_217|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128223": {
+      "content": "<|reserved_special_token_218|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128224": {
+      "content": "<|reserved_special_token_219|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128225": {
+      "content": "<|reserved_special_token_220|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128226": {
+      "content": "<|reserved_special_token_221|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128227": {
+      "content": "<|reserved_special_token_222|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128228": {
+      "content": "<|reserved_special_token_223|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128229": {
+      "content": "<|reserved_special_token_224|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128230": {
+      "content": "<|reserved_special_token_225|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128231": {
+      "content": "<|reserved_special_token_226|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128232": {
+      "content": "<|reserved_special_token_227|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128233": {
+      "content": "<|reserved_special_token_228|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128234": {
+      "content": "<|reserved_special_token_229|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128235": {
+      "content": "<|reserved_special_token_230|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128236": {
+      "content": "<|reserved_special_token_231|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128237": {
+      "content": "<|reserved_special_token_232|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128238": {
+      "content": "<|reserved_special_token_233|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128239": {
+      "content": "<|reserved_special_token_234|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128240": {
+      "content": "<|reserved_special_token_235|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128241": {
+      "content": "<|reserved_special_token_236|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128242": {
+      "content": "<|reserved_special_token_237|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128243": {
+      "content": "<|reserved_special_token_238|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128244": {
+      "content": "<|reserved_special_token_239|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128245": {
+      "content": "<|reserved_special_token_240|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128246": {
+      "content": "<|reserved_special_token_241|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128247": {
+      "content": "<|reserved_special_token_242|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128248": {
+      "content": "<|reserved_special_token_243|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128249": {
+      "content": "<|reserved_special_token_244|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128250": {
+      "content": "<|reserved_special_token_245|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128251": {
+      "content": "<|reserved_special_token_246|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128252": {
+      "content": "<|reserved_special_token_247|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128253": {
+      "content": "<|reserved_special_token_248|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128254": {
+      "content": "<|reserved_special_token_249|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "128255": {
+      "content": "<|reserved_special_token_250|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<|begin_of_text|>",
+  "chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<|eot_id|>",
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}

whisper_model_modified.py

@@ -0,0 +1,144 @@
+####################################################################
+## Built on top of Ultravox: https://github.com/fixie-ai/ultravox ##
+####################################################################
+# modified from https://github.com/huggingface/transformers/blob/main/src/transformers/models/whisper/modeling_whisper.py
+# see this issue for the commentary: https://github.com/huggingface/transformers/issues/25744
+#
+# Copyright 2022 The OpenAI Authors and The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import torch
+import torch.nn as nn
+import transformers
+import transformers.modeling_outputs
+from transformers.models.whisper import modeling_whisper as whisper
+
+
+class WhisperEncoder(whisper.WhisperEncoder):
+    """
+    Encoder portion of OpenAI's Whisper model.
+
+    This implementation is a slightly modified version of HF Transformers' Whisper Encoder, with only a few fixes:
+    1. base_model_prefix updated to allow for doing `.from_pretrained` directly on the encoder
+    2. allow less than 30 second of audio padding to be passed in:
+        - relaxed ValueError check for `input_features` length to be less than or equal to `expected_seq_length` instead of strictly equal
+        - embed_pos is now sliced to match the length of `inputs_embeds`
+
+    Original: https://github.com/huggingface/transformers/blob/main/src/transformers/models/whisper/modeling_whisper.py
+    """
+
+    base_model_prefix = "model.encoder"
+
+    def forward(
+        self,
+        input_features,
+        attention_mask=None,
+        head_mask=None,
+        output_attentions=None,
+        output_hidden_states=None,
+        return_dict=None,
+    ):
+        expected_seq_length = (
+            self.config.max_source_positions
+            * self.conv1.stride[0]
+            * self.conv2.stride[0]
+        )
+        if input_features.shape[-1] > expected_seq_length:
+            raise ValueError(
+                f"Whisper expects the mel input features to be of length {expected_seq_length} or less, but found {input_features.shape[-1]}. Make sure to pad the input mel features to {expected_seq_length}."
+            )
+
+        output_attentions = (
+            output_attentions
+            if output_attentions is not None
+            else self.config.output_attentions
+        )
+        output_hidden_states = (
+            output_hidden_states
+            if output_hidden_states is not None
+            else self.config.output_hidden_states
+        )
+        return_dict = (
+            return_dict if return_dict is not None else self.config.use_return_dict
+        )
+        inputs_embeds = nn.functional.gelu(self.conv1(input_features))
+        inputs_embeds = nn.functional.gelu(self.conv2(inputs_embeds))
+
+        inputs_embeds = inputs_embeds.permute(0, 2, 1)
+        embed_pos = self.embed_positions.weight[: inputs_embeds.size(-2)]
+
+        hidden_states = inputs_embeds + embed_pos
+        hidden_states = nn.functional.dropout(
+            hidden_states, p=self.dropout, training=self.training
+        )
+
+        encoder_states = () if output_hidden_states else None
+        all_attentions = () if output_attentions else None
+
+        # check if head_mask has a correct number of layers specified if desired
+        if head_mask is not None:
+            assert head_mask.size()[0] == (
+                len(self.layers)
+            ), f"The head_mask should be specified for {len(self.layers)} layers, but it is for {head_mask.size()[0]}."
+
+        for idx, encoder_layer in enumerate(self.layers):
+            if output_hidden_states:
+                encoder_states = encoder_states + (hidden_states,)
+            # add LayerDrop (see https://arxiv.org/abs/1909.11556 for description)
+            to_drop = False
+            if self.training:
+                dropout_probability = torch.rand([])
+                if dropout_probability < self.layerdrop:  # skip the layer
+                    to_drop = True
+
+            if to_drop:
+                layer_outputs = (None, None)
+            else:
+                if self.gradient_checkpointing and self.training:
+                    layer_outputs = self._gradient_checkpointing_func(
+                        encoder_layer.__call__,
+                        hidden_states,
+                        None,
+                        (head_mask[idx] if head_mask is not None else None),
+                        output_attentions,
+                    )
+                else:
+                    layer_outputs = encoder_layer(
+                        hidden_states,
+                        None,
+                        layer_head_mask=(
+                            head_mask[idx] if head_mask is not None else None
+                        ),
+                        output_attentions=output_attentions,
+                    )
+
+                hidden_states = layer_outputs[0]
+
+            if output_attentions:
+                all_attentions = all_attentions + (layer_outputs[1],)
+
+        hidden_states = self.layer_norm(hidden_states)
+        if output_hidden_states:
+            encoder_states = encoder_states + (hidden_states,)
+
+        if not return_dict:
+            return tuple(
+                v
+                for v in [hidden_states, encoder_states, all_attentions]
+                if v is not None
+            )
+        return transformers.modeling_outputs.BaseModelOutput(
+            last_hidden_state=hidden_states,
+            hidden_states=encoder_states,
+            attentions=all_attentions,
+        )