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:
- 0d059374fedf75085a0cb9ddfa3437e4cb71ebe04dfae27b6b539f1e4a558c7d
- Size of remote file:
- 137 MB
- SHA256:
- 612d676d22c52953e27e923f8d402cd412548965539516d0c3ec98248e612f7f
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