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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6749f480314f82055f404fc070966fb2e55d7270338400d2cdf37e43fb17f925
- Size of remote file:
- 431 MB
- SHA256:
- d33a0abdf138c713c38f9333abafea255e5a0a50ed0390a0ab43f95b86f8ae85
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