Instructions to use westlake-repl/SaProt_650M_AF2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use westlake-repl/SaProt_650M_AF2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="westlake-repl/SaProt_650M_AF2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("westlake-repl/SaProt_650M_AF2") model = AutoModelForMaskedLM.from_pretrained("westlake-repl/SaProt_650M_AF2") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 319b70945774e6ae64c6f5a4e4c4a63288ea032deb2014abb0081c84f6f0ba5c
- Size of remote file:
- 2.61 GB
- SHA256:
- 513c39088804b74309d961174d5fc7aeabfb9b79d2814cdc7e465d4fe4b9f216
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