Instructions to use Synthyra/DPLM2-650M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/DPLM2-650M with Transformers:
# Load model directly from transformers import AutoTokenizer, EsmForDPLM2 tokenizer = AutoTokenizer.from_pretrained("Synthyra/DPLM2-650M", trust_remote_code=True) model = EsmForDPLM2.from_pretrained("Synthyra/DPLM2-650M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 336 Bytes
259b828 4449110 259b828 | 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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