Arc53/DocsGPT-7B
Arc53/DocsGPT-7B is a 7 billion parameter language model fine-tuned on top of Llama-2-7b, specifically optimized for documentation-based question answering. It excels at providing thorough answers and code examples derived from provided context, making it ideal for developers and technical support. The model was fine-tuned using 50k high-quality examples over 1.5 days on an A10G GPU with LoRA.
Loading preview...
Arc53/DocsGPT-7B: Documentation-Optimized LLM
Arc53/DocsGPT-7B is a 7 billion parameter language model built upon the Llama-2-7b architecture. Its primary differentiation lies in its specialized fine-tuning for documentation-based question answering. The model is designed to provide accurate and comprehensive responses, often including relevant code examples, by leveraging contextual documentation.
Key Capabilities
- Contextual Q&A: Optimized to generate answers directly from provided documentation, ensuring relevance and factual accuracy.
- Developer-Centric: Particularly useful for technical support and developers needing quick, precise information from technical documents.
- Code Example Generation: Capable of producing code snippets within its answers, as demonstrated by its ability to create mock API requests in Python.
- Apache-2.0 License: Freely available for commercial use.
Training Details
The model underwent fine-tuning using 50,000 high-quality examples over 1.5 days on an A10G GPU, employing the LoRA (Low-Rank Adaptation) method. This targeted training process enhances its ability to process and respond to documentation-specific queries.
Prompt Format
DocsGPT-7B expects a specific prompt structure to effectively utilize context:
### Instruction
(your question)
### Context
(relevant documentation + system instructions)
### AnswerThis format ensures the model correctly interprets the user's query and the provided contextual information to generate an informed response.