Phind Codellama 34B - Details

Phind Codellama 34B is a large language model developed by Phind, a company specializing in code generation. With 34b parameters, it is designed for advanced coding tasks and is released under the Llama 2 Community License Agreement (LLAMA-2-CLA). This model focuses on providing precise and efficient code solutions through fine-tuned, instruct-based training.

Phind Codellama 34B is a large language model developed by Phind, a company specializing in code generation. With 34b parameters, it is designed for advanced coding tasks and is released under the Llama 2 Community License Agreement (LLAMA-2-CLA). This model focuses on providing precise and efficient code solutions through fine-tuned, instruct-based training. It is fine-tuned on 1.5B tokens of high-quality programming data, achieving a 73.8% pass@1 on HumanEval, and is instruction-tuned on Alpaca/Vicuna format for ease of use.

Phind Codellama 34B has 34b parameters, placing it in the large model category, which offers strong performance for complex coding tasks but requires significant computational resources. Its 4k context length is suitable for short to moderate tasks, though it may struggle with very long texts. This balance makes it effective for focused code generation while limiting its ability to handle extended contextual requirements.
- Parameter Size: 34b
- Context Length: 4k

Phind Codellama 34B is a model designed for code-related tasks, with possible applications in generating code snippets, assisting with software development workflows, and addressing debugging or optimization challenges. Possible use cases might include automating repetitive coding tasks, suggesting improvements to existing codebases, or supporting developers in learning new programming languages. However, these possible applications require thorough evaluation to ensure they align with specific needs and constraints. The model’s focus on instruction-tuned training suggests it could adapt to various coding scenarios, but further exploration is needed to confirm its effectiveness in real-world settings.
- code generation
- software development assistance
- debugging and code optimization

Phind Codellama 34B is a large language model with possible applications in generating code snippets, assisting with software development workflows, and addressing debugging or optimization challenges. Possible use cases might include automating repetitive coding tasks, suggesting improvements to existing codebases, or supporting developers in learning new programming languages. Possible scenarios could also involve streamlining collaborative coding processes or adapting to niche programming environments. Possible applications in educational settings or rapid prototyping are also under consideration, though these require further exploration. Each possible application must be thoroughly evaluated and tested before deployment to ensure alignment with specific requirements.
- code generation
- software development assistance
- debugging and code optimization

Phind Codellama 34B in its medium q4 version requires a GPU with at least 24GB VRAM for efficient operation, making it suitable for users with mid-range to high-end graphics cards. This quantization balances precision and performance, allowing the model to run on systems with adequate VRAM while maintaining reasonable computational efficiency. Possible applications may vary, but hardware compatibility is critical for smooth execution.
- fp16, q2, q3, q4, q5, q6, q8

Phind Codellama 34B is a large language model developed by Phind, featuring 34b parameters and released under the Llama 2 Community License Agreement, optimized for code generation with a 4k context length. Its design emphasizes efficiency in coding tasks while requiring substantial computational resources for deployment.

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