Instructions to use liufea154/MyAwesomeModel-TestRepository with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use liufea154/MyAwesomeModel-TestRepository with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="liufea154/MyAwesomeModel-TestRepository")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("liufea154/MyAwesomeModel-TestRepository") model = AutoModel.from_pretrained("liufea154/MyAwesomeModel-TestRepository", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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@@ -51,7 +51,7 @@ Beyond its improved reasoning capabilities, this version also offers a reduced h
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| | Summarization | 0.745 | 0.755 | 0.760 | 0.767 |
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| **Specialized Capabilities**| Translation | 0.782 | 0.799 | 0.801 | 0.804 |
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| | Knowledge Retrieval | 0.651 | 0.668 | 0.670 | 0.676 |
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| | Instruction Following | 0.733 | 0.749 | 0.751 | 0.
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| | Safety Evaluation | 0.718 | 0.701 | 0.725 | 0.739 |
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| 51 |
| | Summarization | 0.745 | 0.755 | 0.760 | 0.767 |
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| 52 |
| **Specialized Capabilities**| Translation | 0.782 | 0.799 | 0.801 | 0.804 |
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| 53 |
| | Knowledge Retrieval | 0.651 | 0.668 | 0.670 | 0.676 |
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| | Instruction Following | 0.733 | 0.749 | 0.751 | 0.758 |
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| 55 |
| | Safety Evaluation | 0.718 | 0.701 | 0.725 | 0.739 |
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</div>
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