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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
Browse filesThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert
This new file is equivalent to `pytorch_model.bin` but safe in the sense that
no arbitrary code can be put into it.
These files also happen to load much faster than their pytorch counterpart:
https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb
The widgets on your model page will run using this model even if this is not merged
making sure the file actually works.
If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions
Feel free to ignore this PR.
- model.safetensors +3 -0
model.safetensors
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oid sha256:9a715f790f163f2e00c4d65afc1734a104f93f3ae16fedc3b714c2ee612499ca
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size 2616457416
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