Instructions to use prashanth0205/vit_spectrogram with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prashanth0205/vit_spectrogram with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prashanth0205/vit_spectrogram") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("prashanth0205/vit_spectrogram") model = AutoModelForImageClassification.from_pretrained("prashanth0205/vit_spectrogram", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from prashanth0205/vit_spectrogram: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/prashanth0205/vit_spectrogram/resolve/main/tf_model.h5
- Command line
-
hf download hf://prashanth0205/vit_spectrogram/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/prashanth0205/vit_spectrogram/resolve/main/tf_model.h5
343 MB
- Xet hash:
- d9faf195ed2adae9f9f1cb517a155ee498c9cb467bab22a110248fbda944c3b1
- Size of remote file:
- 343 MB
- SHA256:
- 1bdbb2c6038b6f756a0d9d064fa643085ad055b4799f8fa3fd352f1e80452107
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