Instructions to use facebook/esm2_t30_150M_UR50D with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/esm2_t30_150M_UR50D with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="facebook/esm2_t30_150M_UR50D")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("facebook/esm2_t30_150M_UR50D") model = AutoModelForMaskedLM.from_pretrained("facebook/esm2_t30_150M_UR50D") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 654910d
Upload EsmForMaskedLM
Browse files- config.json +0 -1
- pytorch_model.bin +2 -2
config.json
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"_name_or_path": "/tmp/facebook/esm2_t30_150M_UR50D",
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"architectures": [
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"EsmForMaskedLM"
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"architectures": [
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"EsmForMaskedLM"
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pytorch_model.bin
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