Instructions to use yusr9/radar-encoder-freeze with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yusr9/radar-encoder-freeze with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yusr9/radar-encoder-freeze", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("yusr9/radar-encoder-freeze", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ad4004ce92799d9b4f3703c2be1dd2344dc6993a2bdcf8e3d7d9a5181f19b27
- Size of remote file:
- 5.33 kB
- SHA256:
- 72f85aed90c30dd46b03c09cb9f352557b1b50a657010ece12eb53160f126d6a
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