Model reference · open weights
Qwen2.5-Coder is an open-weight language model from Qwen, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
Qwen2.5-Coder-7B-Instruct 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. - 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 (Non-Embedding): 6.53B - Number of Layers: 28 - Number of Attention Heads (GQA): 28 for Q and 4 for KV - Context Length: Full 131,072 tokens - Please refer to this section for detailed instructions on how to deploy Qwen2.5 for handling long texts. For more details, please refer to our blog, GitHub, Documentation, Arxiv. Requirements The code of Qwen2.5-Coder has been in the latest Hugging face transformers and we advise you to use the latest version of transformers. With transformers<4.37.0, you will encounter the following error: Quickstart Here provides a code snippet with applychattemplate to show you how to load the tokenizer and model and how to generate contents. Processing Long Texts The current config.json is set for context length up to 32,768 tokens. To handle extensive inputs exceeding 32,768 tokens, we utilize YaRN, a technique for enhancing model length extrapolation, ensuring optimal performance on lengt
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | Qwen |
|---|---|
| Type | Language models |
| Parameters (lead) | 7.6B |
| Context | 32k tokens |
| Variants | 4 |
| Runs with | transformers |
| Based on | Qwen/Qwen2.5-Coder-7B |
| Released | 2024-09-17 |
| Popularity | 2.4M downloads / month |
| Likes | 2,113 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
Using it via the API
Once AxForge deploys qwen2-5-coder for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (qwen2-5-coder below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/chat/completions \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"qwen2-5-coder","messages":[{"role":"user","content":"Hello"}]}'
Details
Languages
Tags
Papers
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗