Upload config

README.md

@@ -0,0 +1,201 @@
+---
+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 +1,35 @@
+{
+  "auto_map": {
+    "AutoConfig": "configuration_mobilevlm.MobileVLMConfig"
+  },
+  "freeze_mm_mlp_adapter": false,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "image_aspect_ratio": "pad",
+  "image_grid_pinpoints": null,
+  "initializer_range": 0.02,
+  "intermediate_size": 5632,
+  "max_position_embeddings": 2048,
+  "max_sequence_length": 2048,
+  "mm_hidden_size": 1024,
+  "mm_projector_type": "ldpnet",
+  "mm_use_im_patch_token": false,
+  "mm_use_im_start_end": false,
+  "mm_vision_select_feature": "patch",
+  "mm_vision_select_layer": -2,
+  "mm_vision_tower": "openai/clip-vit-large-patch14-336",
+  "model_type": "mobilevlm",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 16,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "transformers_version": "4.37.2",
+  "tune_mm_mlp_adapter": false,
+  "use_cache": true,
+  "use_mm_proj": true,
+  "vision_tower_type": "clip",
+  "vocab_size": 32000
+}

configuration_mobilevlm.py

@@ -0,0 +1,128 @@
+from typing import List, Optional
+from transformers import PretrainedConfig
+
+config = {
+  "_name_or_path": "mtgv/MobileVLM-1.7B",
+  "architectures": [
+    "MobileLlamaForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "freeze_mm_mlp_adapter": False,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "image_aspect_ratio": "pad",
+  "image_grid_pinpoints": None,
+  "initializer_range": 0.02,
+  "intermediate_size": 5632,
+  "max_position_embeddings": 2048,
+  "max_sequence_length": 2048,
+  "mm_hidden_size": 1024,
+  "mm_projector_type": "ldpnet",
+  "mm_use_im_patch_token": False,
+  "mm_use_im_start_end": False,
+  "mm_vision_select_feature": "patch",
+  "mm_vision_select_layer": -2,
+  "mm_vision_tower": "openai/clip-vit-large-patch14-336",
+  "model_type": "mobilevlm",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "num_key_value_heads": 16,
+  "pad_token_id": 0,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": None,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": False,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.33.1",
+  "tune_mm_mlp_adapter": False,
+  "use_cache": True,
+  "use_mm_proj": True,
+  "vision_tower_type": "clip",
+  "vocab_size": 32000
+}
+
+class MobileVLMConfig(PretrainedConfig):
+    model_type = "mobilevlm"
+
+    def __init__(
+        self,
+        # _name_or_path: str = config["_name_or_path"],
+        architectures: Optional[List[str]] = config["architectures"],
+        bos_token_id: Optional[int] = config["bos_token_id"],
+        eos_token_id: Optional[int] = config["eos_token_id"],
+        freeze_mm_mlp_adapter: Optional[bool] = config["freeze_mm_mlp_adapter"],
+        hidden_act: Optional[str] = config["hidden_act"],
+        hidden_size: Optional[int] = config["hidden_size"],
+        image_aspect_ratio: Optional[str] = config["image_aspect_ratio"],
+        image_grid_pinpoints: Optional[bool] = config["image_grid_pinpoints"],
+        initializer_range: Optional[float] = config["initializer_range"],
+        intermediate_size: Optional[int] = config["intermediate_size"],
+        max_position_embeddings: Optional[int] = config["max_position_embeddings"],
+        max_sequence_length: Optional[int] = config["max_sequence_length"],
+        mm_hidden_size: Optional[int] = config["mm_hidden_size"],
+        mm_projector_type: Optional[str] = config["mm_projector_type"],
+        mm_use_im_patch_token: Optional[bool] = config["mm_use_im_patch_token"],
+        mm_use_im_start_end: Optional[bool] = config["mm_use_im_start_end"],
+        mm_vision_select_feature: Optional[str] = config["mm_vision_select_feature"],
+        mm_vision_select_layer: Optional[int] = config["mm_vision_select_layer"],
+        mm_vision_tower: Optional[str] = config["mm_vision_tower"],
+        # model_type: Optional[str] = config["model_type"],
+        num_attention_heads: Optional[int] = config["num_attention_heads"],
+        num_hidden_layers: Optional[int] = config["num_hidden_layers"],
+        num_key_value_heads: Optional[int] = config["num_key_value_heads"],
+        pad_token_id: Optional[int] = config["pad_token_id"],
+        pretraining_tp: Optional[int] = config["pretraining_tp"],
+        rms_norm_eps: Optional[float] = config["rms_norm_eps"],
+        rope_scaling: Optional[float] = config["rope_scaling"],
+        rope_theta: Optional[float] = config["rope_theta"],
+        tie_word_embeddings: Optional[bool] = config["tie_word_embeddings"],
+        # torch_dtype: Optional[str] = config["torch_dtype"],
+        transformers_version: Optional[str] = config["transformers_version"],
+        tune_mm_mlp_adapter: Optional[bool] = config["tune_mm_mlp_adapter"],
+        use_cache: Optional[bool] = config["use_cache"],
+        use_mm_proj: Optional[bool] = config["use_mm_proj"],
+        vision_tower_type: Optional[str] = config["vision_tower_type"],
+        vocab_size: Optional[int] = config["vocab_size"],
+        **kwargs,
+    ):
+        # self._name_or_path = _name_or_path
+        self.architectures = architectures
+        self.bos_token_id = bos_token_id
+        self.eos_token_id = eos_token_id
+        self.freeze_mm_mlp_adapter = freeze_mm_mlp_adapter
+        self.hidden_act = hidden_act
+        self.hidden_size = hidden_size
+        self.image_aspect_ratio = image_aspect_ratio
+        self.image_grid_pinpoints = image_grid_pinpoints
+        self.initializer_range = initializer_range
+        self.intermediate_size = intermediate_size
+        self.max_position_embeddings = max_position_embeddings
+        self.max_sequence_length = max_sequence_length
+        self.mm_hidden_size = mm_hidden_size
+        self.mm_projector_type = mm_projector_type
+        self.mm_use_im_patch_token = mm_use_im_patch_token
+        self.mm_use_im_start_end = mm_use_im_start_end
+        self.mm_vision_select_feature = mm_vision_select_feature
+        self.mm_vision_select_layer = mm_vision_select_layer
+        self.mm_vision_tower = mm_vision_tower
+        # self.model_type = model_type
+        self.num_attention_heads = num_attention_heads
+        self.num_hidden_layers = num_hidden_layers
+        self.num_key_value_heads = num_key_value_heads
+        self.pad_token_id = pad_token_id
+        self.pretraining_tp = pretraining_tp
+        self.rms_norm_eps = rms_norm_eps
+        self.rope_scaling = rope_scaling
+        self.rope_theta = rope_theta
+        self.tie_word_embeddings = tie_word_embeddings
+        # self.torch_dtype = torch_dtype
+        self.transformers_version = transformers_version
+        self.tune_mm_mlp_adapter = tune_mm_mlp_adapter
+        self.use_cache = use_cache
+        self.use_mm_proj = use_mm_proj
+        self.vision_tower_type = vision_tower_type
+        self.vocab_size = vocab_size
+
+        super().__init__(**kwargs)