Instructions to use virtual-human-chc/prot_xlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use virtual-human-chc/prot_xlnet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="virtual-human-chc/prot_xlnet")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("virtual-human-chc/prot_xlnet") model = AutoModel.from_pretrained("virtual-human-chc/prot_xlnet") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:70ae067b2a1d3a44070356747c22a2e77f478b1693438eee9928c2c4fea20228
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size 1637711612
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