Transformers
PyTorch
esm
biology
protein-language-model
protein-generation
protein-structure
diffusion
Instructions to use airkingbd/dplm2_650m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use airkingbd/dplm2_650m with Transformers:
# Load model directly from transformers import AutoTokenizer, EsmForDPLM2 tokenizer = AutoTokenizer.from_pretrained("airkingbd/dplm2_650m") model = EsmForDPLM2.from_pretrained("airkingbd/dplm2_650m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "aa_cls_token": "<cls_aa>", | |
| "aa_eos_token": "<eos_aa>", | |
| "aa_mask_token": "<mask_aa>", | |
| "aa_unk_token": "<unk_aa>", | |
| "struct_cls_token": "<cls_struct>", | |
| "struct_eos_token": "<eos_struct>", | |
| "struct_mask_token": "<mask_struct>", | |
| "struct_unk_token": "<unk_struct>", | |
| "pad_token": "<pad>" | |
| } | |