Uthaiah/CodeLlama-34b-Instruct-hf
Uthaiah/CodeLlama-34b-Instruct-hf is a 34 billion parameter instruction-tuned generative text model from the Code Llama family, developed by Meta. This model is optimized for general code synthesis and understanding, and excels at instruction following and chat for code-related tasks. It is an auto-regressive language model utilizing an optimized transformer architecture with a 32768 token context length. This specific version is fine-tuned for instruction following and safer deployment in code assistant applications.
Loading preview...
Overview
Uthaiah/CodeLlama-34b-Instruct-hf is a 34 billion parameter instruction-tuned variant of the Code Llama family, developed by Meta. This model is designed for general code synthesis and understanding, and is specifically fine-tuned for instruction following and chat-based interactions. It is an auto-regressive language model built on an optimized transformer architecture, trained between January and July 2023.
Key Capabilities
- Code Completion: Generates code snippets based on context.
- Instruction Following: Responds to and executes instructions for code-related tasks.
- Chat: Engages in conversational interactions for code assistance.
- Code Understanding: Aids in interpreting and analyzing existing code.
Intended Use Cases
This model is intended for commercial and research use in English and relevant programming languages. It is particularly suited for:
- Code Assistant Applications: Providing interactive help and generation for developers.
- Code Generation: Synthesizing new code based on prompts.
- Code Understanding Tasks: Assisting with the interpretation of codebases.
Limitations and Ethical Considerations
As with all large language models, Code Llama may produce inaccurate or objectionable responses. Users are advised to perform safety testing and tuning tailored to their specific applications. The model's use is governed by a custom commercial license from Meta and is not intended for use in languages other than English or in ways that violate applicable laws or Meta's Acceptable Use Policy.