Instructions to use zjunlp/OntoProtein with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zjunlp/OntoProtein with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="zjunlp/OntoProtein")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("zjunlp/OntoProtein") model = AutoModelForMaskedLM.from_pretrained("zjunlp/OntoProtein") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f06e4a1b2bcaa79332bd8e996b83be8cd9dfc390b6b2493b65947eaee28b3d16
- Size of remote file:
- 1.69 GB
- SHA256:
- ae33e3dcaa6e5bc00e7be312eae4dd781f17ebdc943f53b2379923cabb8818d8
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