Instructions to use BenK10/disease-pred with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenK10/disease-pred with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BenK10/disease-pred")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BenK10/disease-pred") model = AutoModelForSequenceClassification.from_pretrained("BenK10/disease-pred", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from BenK10/disease-pred: direct link, hf CLI and curl.
- Browser
- Download file 441 MB
-
https://huggingface.co/BenK10/disease-pred/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://BenK10/disease-pred/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/BenK10/disease-pred/resolve/main/pytorch_model.bin
441 MB
- Xet hash:
- 1d65047bd9ae63fbada477c641cdbf3f8011db1e6ed5113a924dbc5a360c55d1
- Size of remote file:
- 441 MB
- SHA256:
- 2d8d6442f3a1ca3afe810e05eb9a65f8be4e2bb173539bfa48aebf76ab7eea3e
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