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:
- e0d30239b2a9d414235c15063546b5fff04f727f0d73a535de150d40c21d77b6
- Size of remote file:
- 3.38 kB
- SHA256:
- 99edf55fd2fa716bb977cc60dab1a4a009e5321c5a412fa842a1654900072a8a
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