Upload TraVisionForCausalLM

README.md

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+---
+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

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+{
+  "_name_or_path": "TraVisionLM-DPO-v5/checkpoint-30000",
+  "architectures": [
+    "TraVisionForCausalLM"
+  ],
+  "auto_map": {
+    "AutoConfig": "configuration_travisionlm.TraVisionLMConfig",
+    "AutoModelForCausalLM": "ucsahin/TraVisionLM-base--modeling_travisionlm.TraVisionForCausalLM"
+  },
+  "hidden_size": 1280,
+  "ignore_index": -100,
+  "image_token_index": 50257,
+  "model_type": "travisionlm",
+  "num_image_tokens": 256,
+  "projection_dim": 768,
+  "text_config": {
+    "architectures": [
+      "GPT2LMHeadModel"
+    ],
+    "bos_token_id": 0,
+    "eos_token_id": 0,
+    "model_type": "gpt2",
+    "n_ctx": 1024,
+    "n_embd": 1280,
+    "n_head": 20,
+    "n_layer": 36,
+    "pad_token_id": 0,
+    "reorder_and_upcast_attn": true,
+    "scale_attn_by_inverse_layer_idx": true,
+    "task_specific_params": {
+      "text-generation": {
+        "do_sample": true,
+        "max_length": 50
+      }
+    },
+    "torch_dtype": "float32",
+    "vocab_size": 51282
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.45.0.dev0",
+  "vision_config": {
+    "image_size": 256,
+    "model_type": "siglip_vision_model",
+    "projection_dim": 768
+  }
+}

configuration_travisionlm.py

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+"""TraVisionLM configuration"""
+
+from transformers import PretrainedConfig
+from transformers import logging, CONFIG_MAPPING
+import warnings
+
+logger = logging.get_logger(__name__)
+
+class TraVisionLMConfig(PretrainedConfig):
+    model_type = "travisionlm"
+    is_composition = False
+
+    def __init__(
+            self,
+            vision_config=None,
+            text_config=None,
+            ignore_index=-100,
+            image_token_idx=50257,
+            vocab_size=51282,
+            projection_dim=768,
+            hidden_size=1280,
+            **kwargs, 
+    ):
+        self.ignore_index = ignore_index
+        self.image_token_index = image_token_idx
+        self._vocab_size = vocab_size
+        self.projection_dim = projection_dim
+        self.hidden_size = hidden_size
+        self.vision_config = vision_config
+        self.is_encoder_decoder = False
+        if isinstance(self.vision_config, dict):
+            vision_config["model_type"] = (
+                vision_config["model_type"] if "model_type" in vision_config else "siglip_vision_model"
+            )
+            self.vision_config = CONFIG_MAPPING[vision_config["model_type"]](**vision_config)
+        elif vision_config is None:
+            self.vision_config = CONFIG_MAPPING["siglip_vision_model"](
+                attention_dropout=0.0,
+                hidden_act="gelu_pytorch_tanh",
+                hidden_size=768,
+                image_size=256,
+                intermediate_size=3072,
+                layer_norm_eps=1e-06,
+                num_attention_heads=12,
+                num_channels=3,
+                num_hidden_layers=12,
+                patch_size=16,
+            )
+        self.vocab_size = vocab_size
+
+        self.text_config = text_config
+
+        if isinstance(self.text_config, dict):
+            text_config["model_type"] = text_config["model_type"] if "model_type" in text_config else "gpt2"
+            self.text_config = CONFIG_MAPPING[text_config["model_type"]](**text_config)
+        elif text_config is None:
+            self.text_config = CONFIG_MAPPING["gpt2"](
+                activation_function="gelu_new",
+                attn_pdrop=0.1,
+                embd_pdrop=0.1,
+                initializer_range=0.02,
+                layer_norm_epsilon=1e-05,
+                n_ctx=1024,
+                n_embd=1280,
+                n_head=20,
+                n_layer=36,
+                n_positions=1024,
+                reorder_and_upcast_attn=False,
+                resid_pdrop=0.1,
+                scale_attn_by_inverse_layer_idx=False,
+                scale_attn_weights=True,
+                vocab_size=vocab_size
+            )
+        self.num_image_tokens = (self.vision_config.image_size // self.vision_config.patch_size) ** 2
+        self.pad_token_id = self.text_config.pad_token_id
+        self.vision_config.projection_dim = projection_dim
+        super().__init__(**kwargs)
+
+    @property
+    def vocab_size(self):
+        warnings.warn(
+            "The `vocab_size` attribute is deprecated and will be removed in v4.44, Please use `text_config.vocab_size` instead.",
+            FutureWarning,
+        )
+        return self._vocab_size
+
+    @vocab_size.setter
+    def vocab_size(self, value):
+        self._vocab_size = value
+
+    def to_dict(self):
+        output = super().to_dict()
+        output.pop("_vocab_size", None)
+        return output

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 0,
+  "eos_token_id": 0,
+  "pad_token_id": 0,
+  "transformers_version": "4.45.0.dev0"
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a54e47ebd8800d323a53d233f499d6c260c3a11cbb6bd6f8bbd8e8bfb0cbe9e4
+size 3498353344