Instructions to use debbiesoon/prot_bert_bfd-disoRNA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use debbiesoon/prot_bert_bfd-disoRNA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="debbiesoon/prot_bert_bfd-disoRNA")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("debbiesoon/prot_bert_bfd-disoRNA") model = AutoModelForTokenClassification.from_pretrained("debbiesoon/prot_bert_bfd-disoRNA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 900417bb0a32d93f02999edc5a45aa93400225bbb6f4c4738d99626dc2323e8b
- Size of remote file:
- 1.68 GB
- SHA256:
- 46514a30564fca2720320bc56a4d802e8023961097b451fc574ce25781264ba5
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