Add model documentation
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README.md
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# CSQA GPT2-Large Context-Aware Model
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This model is a GPT2-large based model fine-tuned for the CommonsenseQA (CSQA) task with context-aware capabilities.
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## Model Architecture
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This is a multi-component model that includes:
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- **Encoder Model**: GPT2-large based encoder with adapter layers
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- **Latent Model**: GPT2-large based latent representation model with adapter layers
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- **Decoder Model**: GPT2-large based decoder with adapter layers
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- **Projection Layers**: Linear projections between encoder-latent and latent-decoder components
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## Files Structure
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- `encoder.pt` / `encoder_model/`: Encoder component weights and configuration
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- `latent_model.pt` / `latent_model/`: Latent model component weights and configuration
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- `decoder.pt` / `decoder_model/`: Decoder component weights and configuration
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- `encoder_to_latent_model_proj.pt`: Projection layer from encoder to latent model
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- `latent_model_to_decoder_proj.pt`: Projection layer from latent model to decoder
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- `tokenizer/`: GPT2 tokenizer files
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- `config.json`: Model configuration
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## Usage
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This model was trained for the CommonsenseQA task and includes specialized components for context-aware reasoning.
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## Training
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The model was trained in multiple stages on the CommonsenseQA dataset, incorporating context-aware mechanisms to improve reasoning capabilities.
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