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--- |
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language: en |
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license: mit |
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tags: |
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- text-generation |
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- gpt2 |
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- technical-writing |
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- documentation |
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--- |
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# technical_documentation_generator |
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## Overview |
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This model is a fine-tuned version of GPT-2 specifically optimized for generating technical documentation, API references, and software README files. It has been trained on a large corpus of open-source documentation to maintain a professional, objective, and instructional tone. |
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## Model Architecture |
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The model uses a **Decoder-only Transformer** architecture. |
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- **Layers**: 12 Transformer blocks. |
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- **Embedding Dim**: 768. |
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- **Attention**: Masked Multi-Head Self-Attention. |
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- **Objective**: Causal Language Modeling (CLM), predicting the next token $x_i$ based on $x_{<i}$: |
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$$P(x) = \prod_{i=1}^{n} P(x_i | x_1, \dots, x_{i-1})$$ |
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## Intended Use |
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- **Documentation Drafting**: Generating initial templates for function descriptions and class structures. |
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- **Developer Tools**: Integrating into IDEs to suggest comments and docstrings. |
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- **Standardization**: Helping teams maintain a consistent voice across various technical repositories. |
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## Limitations |
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- **Hallucination**: The model may generate syntactically correct but factually incorrect code examples or parameter descriptions. |
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- **Knowledge Cutoff**: It lacks knowledge of software libraries or frameworks released after its last training update in late 2025. |
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- **Logical Flow**: While excellent at sentence-level structure, very long documents may lose coherent logical progression. |
