GenerativeMagic/Llama-Engineer-Evol-7b
GenerativeMagic/Llama-Engineer-Evol-7b is a 7 billion parameter Llama 2 chat instruction-tuned model, further fine-tuned on over 80,000 coding samples. This model specializes in code generation and programming assistance, leveraging datasets like Evol-Instruct-Code-80k-v1 and GPTeacher. It is optimized for direct and helpful responses to coding prompts, with a context length of 4096 tokens.
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Llama-Engineer-Evol-7B: Code-Optimized Llama 2 Variant
GenerativeMagic's Llama-Engineer-Evol-7B is a 7 billion parameter model built upon Meta's Llama 2 chat instruction-tuned architecture. Its primary differentiation lies in extensive fine-tuning on a large corpus of over 80,000 coding samples, specifically designed to enhance its programming capabilities. The training data includes the Evol-Instruct-Code-80k-v1 dataset, a replication of the Evol-Instruct-Code methodology described in the WizardCoder paper, and Teknium's GPTeacher Codegen instructions.
Key Capabilities
- Enhanced Code Generation: Specialized fine-tuning makes it proficient in generating code and assisting with programming tasks.
- Direct and Concise Responses: The recommended prompt format emphasizes direct, helpful, and short responses, ideal for quick programming queries.
- Llama 2 Base: Benefits from the robust foundation of the Llama 2 architecture.
Good For
- Programming Assistance: Ideal for developers seeking quick code snippets, debugging help, or general programming guidance.
- Integration into Developer Tools: Suitable for applications requiring an LLM focused on code-related interactions.
While formal benchmarks are planned for future iterations, the model's development focused on learning and refining the fine-tuning process for code-centric applications. GGML weights are also available for broader deployment.