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:
- e7e4ae66217cfa1bd3ea9e92746314b4df5ee5b42505f88f5e1fc48fe1932a8d
- Size of remote file:
- 595 MB
- SHA256:
- c088e77b5ac2a08ad2c93ae703be78ef6d7b6754369530b1561bad0e95334c5d
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