Instructions to use CATIE-AQ/NERmembert-large-3entities with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CATIE-AQ/NERmembert-large-3entities with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="CATIE-AQ/NERmembert-large-3entities")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("CATIE-AQ/NERmembert-large-3entities") model = AutoModelForTokenClassification.from_pretrained("CATIE-AQ/NERmembert-large-3entities", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -471,11 +471,11 @@ For space reasons, we show only the F1 of the different models. You can see the
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<td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities</a></td>
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<td>F1</td>
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<td><br>0.969</td>
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<td><br>0.919</td>
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<td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmembert-large-4entities">NERmembert-large-4entities</a></td>
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<td><br>0.987</td>
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<td><br>0.976</td>
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<td><br>0.948</td>
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<td><br>0.998</td>
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<td><br>0.902</td>
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<td><br>0.896</td>
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<td rowspan="3"><br><a href="https://hf.co/CATIE-AQ/NERmembert-base-4entities">NERmembert-base-4entities</a></td>
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<td>F1</td>
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<td><br><b>0.969</b></td>
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<td><br><b>0.919</b></td>
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<td><br><b>0.904</b></td>
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<td><br><b>0.989</b></td>
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<td><br><b>0.978</b></td>
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<td rowspan="1"><br><a href="https://hf.co/CATIE-AQ/NERmembert-large-4entities">NERmembert-large-4entities</a></td>
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<td><br><b>0.987</b></td>
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<td><br>0.976</td>
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<td><br>0.948</td>
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<td>F1</td>
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<td><br><b>0.987</b></td>
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<td><br>0.976</td>
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<td><br>0.948</td>
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<td><br>0.998</td>
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