Text Classification
Transformers
Safetensors
English
proto
medical
prototypical-networks
Eval Results (legacy)
Instructions to use row56/ProtoPatient with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use row56/ProtoPatient with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="row56/ProtoPatient")# Load model directly from transformers import ProtoForMultiLabelClassification model = ProtoForMultiLabelClassification.from_pretrained("row56/ProtoPatient", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aea7a2f4c7a3ee3cc0d32479f28ae423fc0f83e7b2228093000c28ccfeb3b871
- Size of remote file:
- 1.11 GB
- SHA256:
- d5a468fd24a7c01f604ca87d3ac77944f932fd9e5c231fffa8d23c7698fa1d23
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