eunomie/qwen2.5-coder-3b-instruct repository overview

⁠Qwen2.5-Coder-3B-Instruct-GGUF

As per the Readme⁠ on HuggingFace:

⁠Introduction

Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). As of now, Qwen2.5-Coder has covered six mainstream model sizes, 0.5, 1.5, 3, 7, 14, 32 billion parameters, to meet the needs of different developers. Qwen2.5-Coder brings the following improvements upon CodeQwen1.5:

• Significantly improvements in code generation, code reasoning and code fixing. Base on the strong Qwen2.5, we scale up the training tokens into 5.5 trillion including source code, text-code grounding, Synthetic data, etc. Qwen2.5-Coder-32B has become the current state-of-the-art open-source codeLLM, with its coding abilities matching those of GPT-4o.
• A more comprehensive foundation for real-world applications such as Code Agents. Not only enhancing coding capabilities but also maintaining its strengths in mathematics and general competencies.

This repo contains the instruction-tuned 3B Qwen2.5-Coder model in the GGUF Format, which has the following features:

• Type: Causal Language Models
• Training Stage: Pretraining & Post-training
• Architecture: transformers with RoPE, SwiGLU, RMSNorm, Attention QKV bias and tied word embeddings
• Number of Parameters: 3.09B
• Number of Paramaters (Non-Embedding): 2.77B
• Number of Layers: 36
• Number of Attention Heads (GQA): 16 for Q and 2 for KV
• Context Length: Full 32,768 tokens
  • Note: Currently, only vLLM supports YARN for length extrapolating. If you want to process sequences up to 131,072 tokens, please refer to non-GGUF models.
• Quantization: q4_K_M, q5_K_M, q6_k, q8_0