Instructions to use AI4Protein/deep_bpe_3200 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AI4Protein/deep_bpe_3200 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AI4Protein/deep_bpe_3200")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AI4Protein/deep_bpe_3200") model = AutoModelForMaskedLM.from_pretrained("AI4Protein/deep_bpe_3200", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd4f5100a22f27f33a6bda9e4df8092d938c11bf31b150ba3af77a7d20afcdc2
- Size of remote file:
- 353 MB
- SHA256:
- 563fdcf168a342e5d88a03712e2eeb3e06aa1e6611109ec19f45c598b201eb68
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