Token Classification
Transformers
PyTorch
Safetensors
French
camembert
Trained with AutoTrain
medical
Instructions to use davanstrien/CamemBERT-MedNERF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/CamemBERT-MedNERF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="davanstrien/CamemBERT-MedNERF")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("davanstrien/CamemBERT-MedNERF") model = AutoModelForTokenClassification.from_pretrained("davanstrien/CamemBERT-MedNERF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from davanstrien/CamemBERT-MedNERF: direct link, hf CLI and curl.
- Browser
- Download file 2.42 MB
-
https://huggingface.co/davanstrien/CamemBERT-MedNERF/resolve/main/tokenizer.json
- Command line
-
hf download hf://davanstrien/CamemBERT-MedNERF/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/davanstrien/CamemBERT-MedNERF/resolve/main/tokenizer.json
2.42 MB
- Xet hash:
- f5eb239b5b0635c8c23a6bc0b5939bf430c7f71eb28e425c2b49132f8c4c31a1
- Size of remote file:
- 2.42 MB
- SHA256:
- aa7ba9e8280c5c6df7e9e224dde795adc6a9d56df77d869093dbb97b3698bb8c
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