Instructions to use laiking/biomedbert-outcomes-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use laiking/biomedbert-outcomes-ner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="laiking/biomedbert-outcomes-ner")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("laiking/biomedbert-outcomes-ner") model = AutoModel.from_pretrained("laiking/biomedbert-outcomes-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5796ebe357175563d5dfe5b6d1a97050787e077857cff9d9dc9c88c0e3a0fd4a
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size 437951328
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