Feature Extraction
Transformers
PyTorch
English
modernbert
genomics
rna
nucleotide
sequence-modeling
biology
bioinformatics
electra
Instructions to use FreakingPotato/RNAElectra with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FreakingPotato/RNAElectra with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="FreakingPotato/RNAElectra")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("FreakingPotato/RNAElectra") model = AutoModel.from_pretrained("FreakingPotato/RNAElectra") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c36e8f14b0c0bbe743de173a88417f2fbfc94d746898b2ed296b6b01c2281f1f
- Size of remote file:
- 369 MB
- SHA256:
- 0c477cad751b23b02b49fbc1dd7e4339fc74191ca082bd5f05eb20d71bf385dc
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