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:
- 16c81c3a10319bcd9485fa50d956ae62bbcc715e73de5529df4fbb19906fa2dc
- Size of remote file:
- 3.06 kB
- SHA256:
- 85c6bd1dcee2672946ee2edeef851d501171f6b4909a207c201850c106813917
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