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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2499ff0750ab772cfe721fa7600ee07724e57fb838867fd5dc70e1e5741f797b
- Size of remote file:
- 369 MB
- SHA256:
- 1a969702e2fa804ade947ab3c221030653a0accbf7a9d1bec72585a9a0bf44e4
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