Instructions to use Synthyra/DPLM2-150M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Synthyra/DPLM2-150M with Transformers:
# Load model directly from transformers import AutoTokenizer, EsmForDPLM2 tokenizer = AutoTokenizer.from_pretrained("Synthyra/DPLM2-150M", trust_remote_code=True) model = EsmForDPLM2.from_pretrained("Synthyra/DPLM2-150M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| """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, ...] = () | |