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
| # Direct runtime dependencies for Synthyra/DPLM2-650M. | |
| # FastPLMs source is embedded in this model repository. | |
| torch>=2.13,<2.14 | |
| transformers>=5.13,<5.14 | |
| huggingface-hub>=0.34,<2 | |
| tokenizers>=0.22,<0.23 | |
| safetensors>=0.5,<1 | |
| numpy>=1.26,<3 | |
| einops>=0.8,<1 | |
| tqdm>=4.67,<5 | |