Instructions to use nepp1d0/prot_bert_karolina_60e_es with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nepp1d0/prot_bert_karolina_60e_es with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nepp1d0/prot_bert_karolina_60e_es")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nepp1d0/prot_bert_karolina_60e_es") model = AutoModelForSequenceClassification.from_pretrained("nepp1d0/prot_bert_karolina_60e_es") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6d5be2474ec137c41ee12fa5f96b233cfc98c2e26cf2dd27c8c956fb856610d
- Size of remote file:
- 1.68 GB
- SHA256:
- 69eaa78b525a9cc4f5950bcb3d02445033a742aa67b32bb6a1c46ffc3dda2284
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