Instructions to use cariai/medslabs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cariai/medslabs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="cariai/medslabs")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("cariai/medslabs") model = AutoModelForTokenClassification.from_pretrained("cariai/medslabs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5474b7abe746f9904aa4e8af8e5c6da0ae4e5c0d0b224c093ff80ffefab0deb4
- Size of remote file:
- 496 MB
- SHA256:
- 0deaf646dfcf875c55feed53b4d97bc82b7493c2890e7079c365f5b23ec31b01
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