Instructions to use shareAI/bimoGPT-llama2-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shareAI/bimoGPT-llama2-13b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="shareAI/bimoGPT-llama2-13b")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shareAI/bimoGPT-llama2-13b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Adding Evaluation Results
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bimoGPT - 一个在llama2 13b基座模型上做中文精细SFT的版本,拥有接近ChatGPT的语气和对话问答能力,以及不错的代码编程能力。
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底座:https://www.codewithgpu.com/m/file/llama2-13b-Chinese-chat (中的llama2-13B-sharegpt_cn-epoch2.zip)
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bimoGPT - 一个在llama2 13b基座模型上做中文精细SFT的版本,拥有接近ChatGPT的语气和对话问答能力,以及不错的代码编程能力。
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底座:https://www.codewithgpu.com/m/file/llama2-13b-Chinese-chat (中的llama2-13B-sharegpt_cn-epoch2.zip)
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_shareAI__bimoGPT-llama2-13b)
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| Metric | Value |
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| Avg. | 46.84 |
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| ARC (25-shot) | 58.79 |
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| HellaSwag (10-shot) | 82.08 |
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| MMLU (5-shot) | 55.6 |
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| TruthfulQA (0-shot) | 37.82 |
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| Winogrande (5-shot) | 76.48 |
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| GSM8K (5-shot) | 11.3 |
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| DROP (3-shot) | 5.84 |
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