Text Classification
Transformers
PyTorch
Safetensors
English
sproto
multi-label-classification
long-tail-learning
medical
clinical-nlp
interpretability
prototypical-networks
ehr
custom_code
Instructions to use DATEXIS/sproto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DATEXIS/sproto with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DATEXIS/sproto", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DATEXIS/sproto", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download overview.png from DATEXIS/sproto: direct link, hf CLI and curl.
- Browser
- Download file 75 kB
-
https://huggingface.co/DATEXIS/sproto/resolve/main/overview.png
- Command line
-
hf download hf://DATEXIS/sproto/overview.png
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curl -L -o overview.png https://huggingface.co/DATEXIS/sproto/resolve/main/overview.png
75 kB
