Instructions to use BAAI/AquilaChat-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/AquilaChat-7B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BAAI/AquilaChat-7B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README_zh.md
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- AquilaChat-7B-01 md5: 0a77901af35d3e5ed16eeafa622e2173
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- AquilaChat-7B-02 md5: 6e84423fe2837c79c0ced6817c316bd4
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Aquila-7B v0.8 在 FlagEval 大模型评测中( “客观”)相比0.7的版本在MMLU_Chinese、TruthfulQA、MMLU上分别10.07%,14.84%和7.94%。
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AquilaChat-7B v0.8 在 FlagEval 大模型评测中( “主观+客观”)相比0.7的版本整体稍有提,其在Chinese-MMLU上提升10%左右,详细评测结果请通过 http://flageval.baai.ac.cn 网站查看。
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历史版本变更详情见:[变更日志](https://huggingface.co/BAAI/AquilaChat-7B/blob/main/change_log.log) 。
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- AquilaChat-7B-01 md5: 0a77901af35d3e5ed16eeafa622e2173
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- AquilaChat-7B-02 md5: 6e84423fe2837c79c0ced6817c316bd4
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Aquila-7B v0.8 在 FlagEval 大模型评测中( “客观”)相比0.7的版本在MMLU_Chinese、TruthfulQA、MMLU上分别提升10.07%,14.84%和7.94%。
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AquilaChat-7B v0.8 在 FlagEval 大模型评测中( “主观+客观”)相比0.7的版本整体稍有提,其在Chinese-MMLU上提升10%左右,详细评测结果请通过 http://flageval.baai.ac.cn 网站查看。
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历史版本变更详情见:[变更日志](https://huggingface.co/BAAI/AquilaChat-7B/blob/main/change_log.log) 。
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