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:
- b418e5b263976b640226c38bec296376073eb2e51bc7abf1b370412fedf9f90b
- Size of remote file:
- 39.5 MB
- SHA256:
- 808cfa67ebb9b7dc7798ec08945d57d3edc6c245acfef5bce3b4329d8ed9ad64
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