Instructions to use sschet/biobert_chemical_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sschet/biobert_chemical_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sschet/biobert_chemical_ner")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("sschet/biobert_chemical_ner") model = AutoModelForTokenClassification.from_pretrained("sschet/biobert_chemical_ner") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c283f2c71a77fa8a9e8e6cdb09091fa6675106928b970b13ccbd8ecab2e32a85
- Size of remote file:
- 431 MB
- SHA256:
- 6e0d5981186ed7a5a464985d958db2c0fd938b042f5f91ce44cb461735deaf64
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