Instructions to use Dauka-transformers/interpro_bert3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dauka-transformers/interpro_bert3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Dauka-transformers/interpro_bert3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Dauka-transformers/interpro_bert3") model = AutoModelForMaskedLM.from_pretrained("Dauka-transformers/interpro_bert3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9268f10f780157582769f367b51c0c92e748da2fbece975ed720b0fea4d0b624
- Size of remote file:
- 4.92 kB
- SHA256:
- 3dffd18810dc8445ed4926635d6da9a77e5b78722a8d9c546f40e6835514ef36
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