TheBloke/CodeLlama-34B-Instruct-fp16
TheBloke/CodeLlama-34B-Instruct-fp16 is a 34 billion parameter instruction-tuned Code Llama model developed by Meta, provided in fp16 Transformers/HF format. This model is specifically designed for instruction following in code assistant and generation applications, leveraging an optimized transformer architecture. It supports a context length of up to 100K tokens at inference time, making it highly capable for complex coding tasks. This variant is optimized for safer deployment and general code synthesis and understanding.
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CodeLlama 34B-Instruct-fp16 Overview
This model is a 34 billion parameter instruction-tuned variant of Meta's Code Llama, provided by TheBloke in fp16 Transformers/HF format. It is built upon an optimized transformer architecture and is specifically fine-tuned for instruction following, making it suitable for code assistant and generation applications. The model supports an impressive context length of up to 100,000 tokens at inference time, allowing it to handle extensive codebases and complex programming prompts.
Key Capabilities
- Instruction Following: Designed for accurate interpretation and execution of coding instructions.
- Code Synthesis and Understanding: Excels at generating and comprehending various programming languages.
- Extended Context Window: Supports up to 100K tokens, beneficial for large code projects and detailed requests.
- Optimized for Safety: The Instruct variant is intended for safer deployment in code-related applications.
When to Use This Model
- Code Generation: Ideal for generating code snippets, functions, or entire programs based on natural language instructions.
- Code Assistance: Useful for intelligent code completion, debugging, and refactoring suggestions.
- Educational Tools: Can serve as a powerful backend for programming tutors or learning platforms.
- Research and Development: Suitable for exploring advanced code-centric AI applications requiring high parameter count and instruction adherence.
This model requires trust_remote_code=True when loading due to specific RoPE Theta value changes for correct results.