Instructions to use toolevalxm/MedicalNLP-Pro-TestRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use toolevalxm/MedicalNLP-Pro-TestRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="toolevalxm/MedicalNLP-Pro-TestRepo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("toolevalxm/MedicalNLP-Pro-TestRepo") model = AutoModelForMaskedLM.from_pretrained("toolevalxm/MedicalNLP-Pro-TestRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from toolevalxm/MedicalNLP-Pro-TestRepo: direct link, hf CLI and curl.
- Browser
- Download file 24 Bytes
-
https://huggingface.co/toolevalxm/MedicalNLP-Pro-TestRepo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://toolevalxm/MedicalNLP-Pro-TestRepo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/toolevalxm/MedicalNLP-Pro-TestRepo/resolve/main/pytorch_model.bin
24 Bytes
- Xet hash:
- 77c37dd462eb28e2a7f0393a2a2926dcf6b23c190f8b10cc9545b2f443ea08e1
- Size of remote file:
- 24 Bytes
- SHA256:
- dccaf66b5346cce0dcef55de3c031d1d37e3fef81e29047948d5fd78bbd4cd9b
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