Instructions to use Synthyra/FastESM2_650 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/FastESM2_650 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Synthyra/FastESM2_650", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Synthyra/FastESM2_650", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2ac38ecd9dd370fbfc16d32783f0ea6d201c0bce6081d35d4c776ef1e838938b
- Size of remote file:
- 2.6 GB
- SHA256:
- 2ebc7d45f53e25d4c130e392df06ba76bb14f46c966a0ee87f8f004296c63b78
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