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:
- 8762aac25180146874a4b66e6a2f877ba6c1570e464640edf157cd3004fa07ff
- Size of remote file:
- 14.2 kB
- SHA256:
- 9196a1e708bf24d6abba41cce3f8558820acc3e50f9394c5955e29eb41ffea3d
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