hemlang/Hemlock2-Coder-7B
Hemlock2-Coder-7B is a 7.6 billion parameter language model developed by hemlang, fine-tuned from Qwen/Qwen2.5-Coder-7B-Instruct using the ORPO training mode. With a context length of 32768 tokens, this model is specifically optimized for code generation and understanding tasks. Its specialized training makes it highly effective for developers requiring robust coding assistance and instruction following.
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Hemlock2-Coder-7B Overview
Hemlock2-Coder-7B is a 7.6 billion parameter language model developed by hemlang, built upon the Qwen/Qwen2.5-Coder-7B-Instruct base model. It was fine-tuned using the ORPO training mode over 2 epochs, with a maximum sequence length of 2048 during training, though it supports a 32768 token context length for inference. This model leverages 4-bit (NF4) quantization and LoRA (Rank 128, Alpha 64) for efficient performance.
Key Capabilities
- Code Generation: Optimized for generating high-quality code across various programming languages.
- Instruction Following: Excels at understanding and executing complex coding instructions.
- Efficient Performance: Benefits from 4-bit quantization and LoRA for reduced resource usage.
Good for
- Developers needing an instruction-tuned model for coding tasks.
- Applications requiring robust code completion and generation.
- Environments where efficient deployment of a 7B-class model is crucial.