Token Classification
Transformers
PyTorch
English
xlm-roberta
nlp
roberta
xlmr
classifier
aer
narrative
entity recognition
Instructions to use altsoph/xlmr-AER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use altsoph/xlmr-AER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="altsoph/xlmr-AER")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("altsoph/xlmr-AER") model = AutoModelForTokenClassification.from_pretrained("altsoph/xlmr-AER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from altsoph/xlmr-AER: direct link, hf CLI and curl.
- Browser
- Download file 2.24 GB
-
https://huggingface.co/altsoph/xlmr-AER/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://altsoph/xlmr-AER/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/altsoph/xlmr-AER/resolve/main/pytorch_model.bin
2.24 GB
- Xet hash:
- 3ae6c44f63454b6cc6fdb5c61ec3ea0e9df0d0b3bd210597ce08d721e0f9b435
- Size of remote file:
- 2.24 GB
- SHA256:
- a0135e2cecac64fbc4d0663628550be9c5996e666101d740dd756303bffa86a2
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