Instructions to use coastalcph/fairlex-ecthr-minilm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use coastalcph/fairlex-ecthr-minilm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="coastalcph/fairlex-ecthr-minilm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("coastalcph/fairlex-ecthr-minilm") model = AutoModelForMaskedLM.from_pretrained("coastalcph/fairlex-ecthr-minilm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Corrected tiny typo in loading the model
Browse filesFixed a tiny typo at the section _Load Pretrained Model_
README.md
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@@ -41,8 +41,8 @@ For the English datasets (ECtHR, SCOTUS) and the one distilled from XLM-R (Conne
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```python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("coastalcph/fairlex-ecthr-
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model = AutoModel.from_pretrained("coastalcph/fairlex-ecthr-
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```
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```python
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from transformers import AutoTokenizer, AutoModel
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tokenizer = AutoTokenizer.from_pretrained("coastalcph/fairlex-ecthr-minilm")
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model = AutoModel.from_pretrained("coastalcph/fairlex-ecthr-minilm")
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```
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