Instructions to use westlake-repl/SaProt_35M_AF2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use westlake-repl/SaProt_35M_AF2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="westlake-repl/SaProt_35M_AF2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("westlake-repl/SaProt_35M_AF2") model = AutoModelForMaskedLM.from_pretrained("westlake-repl/SaProt_35M_AF2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bec7f49c41a37f94b5dfd9d96cc65b612c1ac7271f322ad18b8bb17185980f75
- Size of remote file:
- 135 MB
- SHA256:
- 7adb9d736184d14c83eab30d03e6cc3183c01b71a99776d2c52de7ef0278883a
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