Instructions to use anrilombard/bert-finetuned-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anrilombard/bert-finetuned-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="anrilombard/bert-finetuned-ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("anrilombard/bert-finetuned-ner") model = AutoModelForTokenClassification.from_pretrained("anrilombard/bert-finetuned-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from anrilombard/bert-finetuned-ner: direct link, hf CLI and curl.
- Browser
- Download file 431 MB
-
https://huggingface.co/anrilombard/bert-finetuned-ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://anrilombard/bert-finetuned-ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/anrilombard/bert-finetuned-ner/resolve/main/pytorch_model.bin
431 MB
- Xet hash:
- 7b09ea0637d4d8509ec3598212fb2d2b364f0b39e35425d3248620550f7ee256
- Size of remote file:
- 431 MB
- SHA256:
- 2e9f9d2946b508414cbfb16d967c66f752cdc7c2a830a530d930a322ad3678f5
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