Instructions to use yusr9/RADAR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yusr9/RADAR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yusr9/RADAR", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("yusr9/RADAR", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0ae63c5d93e98f9f6fd1a3284549c91088b9d9ddd9d720d05d9570cd562c5176
- Size of remote file:
- 5.27 kB
- SHA256:
- 08bc9ddf6733a5e7d343d9661c4d7948a145f00334866b20c7c4ce65b19f7f29
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