Instructions to use YYLY66/mRNABERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YYLY66/mRNABERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="YYLY66/mRNABERT", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("YYLY66/mRNABERT", trust_remote_code=True) model = AutoModelForMaskedLM.from_pretrained("YYLY66/mRNABERT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 082f89a7b1f781b4af4f66541f0c2247b5d79e98e4a481e0696c2b8b1c3fc8a3
- Size of remote file:
- 456 MB
- SHA256:
- cb2eb64831a494d4cac14acb5df908f734e088c4d62256ac3e42cada60c3bf75
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