Instructions to use nepp1d0/Bert-pretrained-proteinBindingDB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nepp1d0/Bert-pretrained-proteinBindingDB with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nepp1d0/Bert-pretrained-proteinBindingDB")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nepp1d0/Bert-pretrained-proteinBindingDB") model = AutoModelForSequenceClassification.from_pretrained("nepp1d0/Bert-pretrained-proteinBindingDB", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7408f73ca7308daffd73173863e4caf1a5a6bc22abba08be7b5172c4fb6a7d22
- Size of remote file:
- 175 MB
- SHA256:
- 99623a0b6f414fffce68f2cd07bf50cd9f6e4f19718a8a7a8e054dac4bd14081
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