Instructions to use CofeAI/FLM-2-52B-Instruct-2407 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CofeAI/FLM-2-52B-Instruct-2407 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="CofeAI/FLM-2-52B-Instruct-2407", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("CofeAI/FLM-2-52B-Instruct-2407", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -52,6 +52,8 @@ We evaluate the alignment performance of FLM-2-52B-Instruct-2407 in Chinese acro
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| chatglm-turbo | 6.36 | 4.88 | 5.09 |<u>7.50</u>| 7.03 |<u>8.45</u>| 8.05 | 7.67 | 7.70 |
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| FLM-2-52B-Instruct-2407 | 6.23 | 3.79 |<u>5.15</u>| **7.69** | **7.86** |<u>8.45</u>|<u>8.17</u>|<u>7.88</u>|<u>7.85</u>|
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# Citation
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| chatglm-turbo | 6.36 | 4.88 | 5.09 |<u>7.50</u>| 7.03 |<u>8.45</u>| 8.05 | 7.67 | 7.70 |
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| FLM-2-52B-Instruct-2407 | 6.23 | 3.79 |<u>5.15</u>| **7.69** | **7.86** |<u>8.45</u>|<u>8.17</u>|<u>7.88</u>|<u>7.85</u>|
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# Acknowledgements
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This work was supported by the National Science and Technology Major Project (No. 2022ZD0116314).
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# Citation
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