Instructions to use nepp1d0/prot_bert_classification_finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nepp1d0/prot_bert_classification_finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nepp1d0/prot_bert_classification_finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nepp1d0/prot_bert_classification_finetuned") model = AutoModelForSequenceClassification.from_pretrained("nepp1d0/prot_bert_classification_finetuned") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a53dbf46ff1b2125f93b64c2b80ad5a2a30eb17586a0f5ab1346b2a2bed04aa1
- Size of remote file:
- 1.68 GB
- SHA256:
- ed809e8e44eca4530b77c5286b0c900e0dc735b15299125b86a50ecf0495f7f5
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