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:
- 93e571debdb1fead382ce68ffe940e222cdab3df2c6f8f07c1d7c47803dd7f63
- Size of remote file:
- 2.62 kB
- SHA256:
- 31f347feb1ea87f5ef3d77d05496496e14ea5b0b822f500ab63251e9baf04c3c
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