Qwen2.5 Coder 7B Instruct The model used alvarobartt/openhermes preferences coding as calibration dataset Introduction Qwen2.5 Coder is the latest series of Code Specific Qwen large language models (formerly known as CodeQwen). For Qwen2.5 Coder, we release three base language models and instruction tuned language models, 1.5, 7 and 32 (coming soon) billion parameters. 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. 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. Long context Support up to 128K tokens. This repo contains the instruction tuned 7B Qwen2.5 Coder model , which has the following features: Type: Causal Language Models Training Stage: Pretraining & Post training Architecture: transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias Number of Parameters: 7.61B Number of Paramaters (…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy