Instructions to use roscazo/ner_ANAT_DISO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roscazo/ner_ANAT_DISO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="roscazo/ner_ANAT_DISO")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("roscazo/ner_ANAT_DISO") model = AutoModelForTokenClassification.from_pretrained("roscazo/ner_ANAT_DISO", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from roscazo/ner_ANAT_DISO: direct link, hf CLI and curl.
- Browser
- Download file 2.24 MB
-
https://huggingface.co/roscazo/ner_ANAT_DISO/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
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hf download hf://roscazo/ner_ANAT_DISO@refs/pr/2/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/roscazo/ner_ANAT_DISO/resolve/refs%2Fpr%2F2/tokenizer.json
2.24 MB
File too large to display, you can check the raw version instead.