Instructions to use Synthyra/ESMplusplus_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/ESMplusplus_large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Synthyra/ESMplusplus_large", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Synthyra/ESMplusplus_large", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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fff6702 ee7f2fd fff6702 | 1 2 3 4 5 6 7 8 9 10 11 12 | """Lazy model-family namespace for FastPLMs.
Model classes are resolved through Transformers AutoClasses and the typed
registry. Importing this package therefore does not load checkpoints, create
tokenizers, compile kernels, or initialize an accelerator runtime.
"""
from __future__ import annotations
__all__: tuple[str, ...] = ()
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