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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]

backbone.py

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+import torch
+
+from .modules import ResBlock
+
+
+class MyBackbone(torch.nn.Module):
+
+    def __init__(
+        self,
+        num_layers: int = 2,
+        input_dim: int = 2,
+        hidden_dim: int = 128,
+        output_dim: int = 2,
+    ):
+        super().__init__()
+        self.num_layers = num_layers
+        self.input_dim = input_dim
+        self.hidden_dim = hidden_dim
+        self.output_dim = output_dim
+
+        # Define the layers of the backbone
+        layers = [torch.nn.Linear(input_dim, hidden_dim)]
+        for _ in range(num_layers):
+            layers.append(ResBlock(hidden_dim))
+        layers.append(torch.nn.Linear(hidden_dim, output_dim))
+        
+        self.model = torch.nn.Sequential(*layers)
+    
+    def forward(self, x):
+        # Forward pass through the backbone
+        return self.model(x)
+ 

config.json

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+{
+  "architectures": [
+    "MyModel"
+  ],
+  "hidden_dim": 128,
+  "input_dim": 2,
+  "model_type": "my_model",
+  "num_layers": 2,
+  "output_dim": 2,
+  "torch_dtype": "float32",
+  "transformers_version": "4.51.3"
+}

modeling.py

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+import transformers
+
+from .backbone import MyBackbone
+
+
+class MyModelConfig(transformers.PretrainedConfig):
+
+    model_type = "my_model"
+    auto_map = {
+        "AutoConfig": "modeling.MyModelConfig",
+        "AutoModel": "modeling.MyModel",
+    }
+
+    def __init__(
+        self,
+        num_layers: int = 2,
+        input_dim: int = 2,
+        hidden_dim: int = 128,
+        output_dim: int = 2,
+        **kwargs
+    ):
+        super().__init__(**kwargs)
+        self.num_layers = num_layers
+        self.input_dim = input_dim
+        self.hidden_dim = hidden_dim
+        self.output_dim = output_dim
+
+class MyModel(transformers.PreTrainedModel):
+
+    config_class = MyModelConfig
+
+    def __init__(self, config: MyModelConfig):
+        super().__init__(config)
+        self.config = config
+        self.backbone = MyBackbone(
+            num_layers=config.num_layers,
+            input_dim=config.input_dim,
+            hidden_dim=config.hidden_dim,
+            output_dim=config.output_dim,
+        )
+
+    def forward(self, inputs):
+        # Forward pass through the backbone
+        outputs = self.backbone(inputs)
+        return outputs

modules.py

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+import torch
+
+class ResBlock(torch.nn.Module):
+
+    def __init__(self, dim: int):
+        super().__init__()
+        self.fc = torch.nn.Linear(dim, dim)
+        self.relu = torch.nn.ReLU()
+
+    def forward(self, x):
+        # Apply the first linear layer
+        z = self.fc(x)
+        # Apply ReLU activation
+        z = self.relu(z)
+        return x + z

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:26b9155a5ae09cb107090ab90f216cee146012b9c259624b4f2d3b4605b0fd0d
+size 137864