55 lines
2.6 KiB
Markdown
55 lines
2.6 KiB
Markdown
---
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license: other
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language:
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- en
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pipeline_tag: text-generation
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inference: false
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tags:
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- transformers
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- gguf
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- imatrix
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- Qwen2.5-Coder-1.5B
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---
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Quantizations of https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B
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### Inference Clients/UIs
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* [llama.cpp](https://github.com/ggerganov/llama.cpp)
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* [KoboldCPP](https://github.com/LostRuins/koboldcpp)
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* [ollama](https://github.com/ollama/ollama)
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* [text-generation-webui](https://github.com/oobabooga/text-generation-webui)
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* [GPT4All](https://github.com/nomic-ai/gpt4all)
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* [jan](https://github.com/janhq/jan)
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---
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# From original readme
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## Introduction
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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:
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- 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.
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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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**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
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- Architecture: transformers with RoPE, SwiGLU, RMSNorm, Attention QKV bias and tied word embeddings
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- Number of Parameters: 1.54B
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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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For more details, please refer to our [blog](https://qwenlm.github.io/blog/qwen2.5-coder-family/), [GitHub](https://github.com/QwenLM/Qwen2.5-Coder), [Documentation](https://qwen.readthedocs.io/en/latest/), [Arxiv](https://arxiv.org/abs/2409.12186).
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## Requirements
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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`.
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With `transformers<4.37.0`, you will encounter the following error:
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```
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KeyError: 'qwen2'
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``` |