Instructions to use philschmid/distilroberta-base-ner-wikiann-conll2003-3-class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/distilroberta-base-ner-wikiann-conll2003-3-class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="philschmid/distilroberta-base-ner-wikiann-conll2003-3-class")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("philschmid/distilroberta-base-ner-wikiann-conll2003-3-class") model = AutoModelForTokenClassification.from_pretrained("philschmid/distilroberta-base-ner-wikiann-conll2003-3-class", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from philschmid/distilroberta-base-ner-wikiann-conll2003-3-class: direct link, hf CLI and curl.
- Browser
- Download file 326 MB
-
https://huggingface.co/philschmid/distilroberta-base-ner-wikiann-conll2003-3-class/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://philschmid/distilroberta-base-ner-wikiann-conll2003-3-class/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/philschmid/distilroberta-base-ner-wikiann-conll2003-3-class/resolve/main/pytorch_model.bin
326 MB
- Xet hash:
- 92b5cb14195b8e7589d6667953ce4c61215453fb0f738b4dd4f13f999f8bbcff
- Size of remote file:
- 326 MB
- SHA256:
- 04fe971151b3871aafe85511a85565218715f90c7c1e209861edae0a8aecc826
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