Instructions to use yusr9/radar-encoder-freeze-raid with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yusr9/radar-encoder-freeze-raid with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yusr9/radar-encoder-freeze-raid", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("yusr9/radar-encoder-freeze-raid", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa7352eee158ae14f0adb24b11917ae15052084cf510e5d25b204fd00939e371
- Size of remote file:
- 39.5 MB
- SHA256:
- 4b213b8b5a236f288be0f02889430ccf02ea49d247884011c8e67494e5d566ec
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