Instructions to use raynardj/roberta-pubmed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raynardj/roberta-pubmed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="raynardj/roberta-pubmed")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("raynardj/roberta-pubmed") model = AutoModelForMaskedLM.from_pretrained("raynardj/roberta-pubmed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from raynardj/roberta-pubmed: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/raynardj/roberta-pubmed/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://raynardj/roberta-pubmed/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/raynardj/roberta-pubmed/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 9367b0a37f9b0fec2d7cad6a57c276b571d319f070a79e4de49b6273f41a480a
- Size of remote file:
- 499 MB
- SHA256:
- 15341e4238a7b686be1e1d4afb0276f46255bf38a89dd3a14b7db0e86ef8df0a
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