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:
- 86adbf601b0ca70a58d8df697c5179fdff887f127386e4d87e63147395d9261c
- Size of remote file:
- 2.61 GB
- SHA256:
- bc110567bc75511c7f46eb3e7d109fd6e81051baad471e22c5306ed71653cd52
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