Instructions to use codefuse-ai/CodeFuse-DevOps-Model-7B-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codefuse-ai/CodeFuse-DevOps-Model-7B-Base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="codefuse-ai/CodeFuse-DevOps-Model-7B-Base", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("codefuse-ai/CodeFuse-DevOps-Model-7B-Base", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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license: other
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# Acknowledgments
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This project refers to the following open source projects, and I would like to express my gratitude to the relevant projects and research and development personnel.
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- [LLaMA-Efficient-Tuning](https://github.com/hiyouga/LLaMA-Efficient-Tuning)
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- [QwenLM](https://github.com/QwenLM)
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license: other
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language:
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- zh
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tags:
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- Text Generation
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- LLM
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<div align="center">
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<h1>
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# Acknowledgments
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This project refers to the following open source projects, and I would like to express my gratitude to the relevant projects and research and development personnel.
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- [LLaMA-Efficient-Tuning](https://github.com/hiyouga/LLaMA-Efficient-Tuning)
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- [QwenLM](https://github.com/QwenLM)
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