Instructions to use sschet/biobert_ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sschet/biobert_ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="sschet/biobert_ner")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("sschet/biobert_ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 007e34a0cdb2d1bf68c08954718ea40063421eb95889438fb2a862b2bca375f3
- Size of remote file:
- 1.21 kB
- SHA256:
- c8d04d6c200da456bab414d4ce7ba1a7473ac55f2c50f2a14f43782b55cbb225
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