Instructions to use Yanzhu/bertweetfr_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yanzhu/bertweetfr_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Yanzhu/bertweetfr_ner")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Yanzhu/bertweetfr_ner") model = AutoModelForTokenClassification.from_pretrained("Yanzhu/bertweetfr_ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Yanzhu/bertweetfr_ner: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/Yanzhu/bertweetfr_ner/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Yanzhu/bertweetfr_ner/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Yanzhu/bertweetfr_ner/resolve/main/pytorch_model.bin
440 MB
- Xet hash:
- 8188e818095b7a1d66f559be2a3c348a735a44ef9eb20edf3a179609af803a9e
- Size of remote file:
- 440 MB
- SHA256:
- 0ab2fc267bb4ddd1d91295dee85b69bf3af0c05ab7857e417272a5b582be4c19
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