Instructions to use ucabqfe/roberta_PER_bio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ucabqfe/roberta_PER_bio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="ucabqfe/roberta_PER_bio")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("ucabqfe/roberta_PER_bio") model = AutoModelForTokenClassification.from_pretrained("ucabqfe/roberta_PER_bio", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ucabqfe/roberta_PER_bio: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/ucabqfe/roberta_PER_bio/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ucabqfe/roberta_PER_bio/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ucabqfe/roberta_PER_bio/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- f483814f644d7d0e9734174d3cef5f6f9a31ab390d25d9d6ae717df7894095d9
- Size of remote file:
- 496 MB
- SHA256:
- 3062e5f6593312b392e155202ba5ce837000a87d051a8a5ba2f8b5baa9c222d6
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