Instructions to use Goorm-AI-04/MobileNetV2-Doppler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Goorm-AI-04/MobileNetV2-Doppler with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Goorm-AI-04/MobileNetV2-Doppler") 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("Goorm-AI-04/MobileNetV2-Doppler") model = AutoModelForImageClassification.from_pretrained("Goorm-AI-04/MobileNetV2-Doppler", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Goorm-AI-04/MobileNetV2-Doppler: direct link, hf CLI and curl.
- Browser
- Download file 9.22 MB
-
https://huggingface.co/Goorm-AI-04/MobileNetV2-Doppler/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Goorm-AI-04/MobileNetV2-Doppler/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Goorm-AI-04/MobileNetV2-Doppler/resolve/main/pytorch_model.bin
9.22 MB
- Xet hash:
- 3c559d03e7d4db1c72fe4069237c09280748a40325e32841f4b5f8e6b5493112
- Size of remote file:
- 9.22 MB
- SHA256:
- 70dd4eee10a7c19bdb29114ee958ae49d5dcab2a7ff0f69914a22217d7221d8d
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