Transformers
PyTorch
esm
biology
protein-language-model
protein-generation
protein-structure
diffusion
bitwise-modeling
Instructions to use airkingbd/dplm2_bit_650m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use airkingbd/dplm2_bit_650m with Transformers:
# Load model directly from transformers import AutoTokenizer, EsmForDPLM2Bit tokenizer = AutoTokenizer.from_pretrained("airkingbd/dplm2_bit_650m") model = EsmForDPLM2Bit.from_pretrained("airkingbd/dplm2_bit_650m") - Notebooks
- Google Colab
- Kaggle
Add model card
#1
by nielsr HF Staff - opened
This PR adds a model card, ensuring the model can be found via the feature-extraction pipeline. It also specifies the library and links to the project page and code repository.