Instructions to use AlpineHealth/socialsupport-3class-sdoh-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlpineHealth/socialsupport-3class-sdoh-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AlpineHealth/socialsupport-3class-sdoh-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AlpineHealth/socialsupport-3class-sdoh-model") model = AutoModelForSequenceClassification.from_pretrained("AlpineHealth/socialsupport-3class-sdoh-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AlpineHealth/socialsupport-3class-sdoh-model: direct link, hf CLI and curl.
- Browser
- Download file 738 MB
-
https://huggingface.co/AlpineHealth/socialsupport-3class-sdoh-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://AlpineHealth/socialsupport-3class-sdoh-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AlpineHealth/socialsupport-3class-sdoh-model/resolve/main/pytorch_model.bin
738 MB
- Xet hash:
- 5c8b6855921dd9faeec0ecc78a958a947a8e6ff650099dc0eb04c8eba3277580
- Size of remote file:
- 738 MB
- SHA256:
- 97ea61b0b9e4de096dc3db5597cda899a46f34c6ffa12820e536f8dc80831da1
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