Feature Extraction
Transformers
PyTorch
Safetensors
boltz2_automodel
protein-language-model
fastplms
custom_code
Instructions to use Synthyra/Boltz2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/Boltz2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Synthyra/Boltz2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Synthyra/Boltz2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 336 Bytes
c65e212 4c8d0e0 c65e212 | 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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