feihu.hf
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update README & LICENSE
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README.md
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---
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license: apache-2.0
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language:
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- en
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base_model:
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tags:
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- code
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- qwen
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- codeqwen
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- qwen-coder
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---
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# Qwen2.5-Coder-1.5B
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- 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.
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- **Long-context Support** up to 128K tokens and can generate up to 8K tokens.
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**This repo contains the 1.5B Qwen2.5-Coder model**, which has the following features:
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- Type: Causal Language Models
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- Training Stage: Pretraining & Post-training
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- Number of Paramaters (Non-Embedding): 1.31B
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- Number of Layers: 28
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- Number of Attention Heads (GQA): 12 for Q and 2 for KV
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- Context Length: Full 32,768 tokens
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**We do not recommend using base language models for conversations.** Instead, you can apply post-training, e.g., SFT, RLHF, continued pretraining, etc., or fill in the middle tasks on this model.
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KeyError: 'qwen2'
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```
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## Evaluation & Performance
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Detailed evaluation results are reported in this [📑 blog](https://qwenlm.github.io/blog/qwen2.5-coder/).
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journal={arXiv preprint arXiv:2407.10671},
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year={2024}
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}
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```
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-
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-
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---
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license: apache-2.0
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license_link: https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B/blob/main/LICENSE
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language:
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- en
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base_model:
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tags:
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- code
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- qwen
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- qwen-coder
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- codeqwen
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---
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# Qwen2.5-Coder-1.5B
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- 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.
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- **Long-context Support** up to 128K tokens and can generate up to 8K tokens.
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+
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**This repo contains the 1.5B Qwen2.5-Coder model**, which has the following features:
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- Type: Causal Language Models
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- Training Stage: Pretraining & Post-training
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- Number of Paramaters (Non-Embedding): 1.31B
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- Number of Layers: 28
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- Number of Attention Heads (GQA): 12 for Q and 2 for KV
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- Context Length: Full 32,768 tokens
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**We do not recommend using base language models for conversations.** Instead, you can apply post-training, e.g., SFT, RLHF, continued pretraining, etc., or fill in the middle tasks on this model.
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KeyError: 'qwen2'
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```
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## Evaluation & Performance
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Detailed evaluation results are reported in this [📑 blog](https://qwenlm.github.io/blog/qwen2.5-coder/).
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journal={arXiv preprint arXiv:2407.10671},
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year={2024}
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}
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```
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