Text Classification
Transformers
PyTorch
bert
rna
gquad
g-quadruplex
transformer
genomics
rna-biology
Instructions to use aimedica/g4mer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aimedica/g4mer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aimedica/g4mer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aimedica/g4mer") model = AutoModelForSequenceClassification.from_pretrained("aimedica/g4mer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4413680b3b3c114532251ff81afdadc0e5eb2b981205cf4eef07362f87724681
- Size of remote file:
- 187 MB
- SHA256:
- 223cff88efd76d88ce9f08159565c14ef3a8410961ef3de7151a701b1bf07f26
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