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
- Xet hash:
- eb6239ad4ceffd5d878c5f2cabcf4a90cf99b81bd5f27ffe65dc75a560bc9d39
- Size of remote file:
- 2.69 GB
- SHA256:
- 8d6e08cc05e4858064a714013c74cc88c9caa2cc8b12c34605a3c24bcd877cfb
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