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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1970c2ad26dc740d6d6871c5b020e2983bfc3213d02669bc3c96f13b6651b45a
- Size of remote file:
- 16.2 MB
- SHA256:
- 83a5545665cd1cfd5f1a357671b3ae1aae543f6fc9065ec1313525c72e09fda8
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