Instructions to use AmelieSchreiber/esm_interact with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AmelieSchreiber/esm_interact with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="AmelieSchreiber/esm_interact")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AmelieSchreiber/esm_interact") model = AutoModelForMaskedLM.from_pretrained("AmelieSchreiber/esm_interact", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f5094e876d37354fce65aabb31fb0c765e2c000b1023379bffa1b9dda4f6264
- Size of remote file:
- 4.54 kB
- SHA256:
- 4f73bb2c61584271c870307947b33c88e57d01f979bbd9dcdf830c49ce360baf
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