Instructions to use hf-tiny-model-private/tiny-random-MobileNetV1ForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MobileNetV1ForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-tiny-model-private/tiny-random-MobileNetV1ForImageClassification") 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("hf-tiny-model-private/tiny-random-MobileNetV1ForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-MobileNetV1ForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-MobileNetV1ForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 894 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-MobileNetV1ForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-MobileNetV1ForImageClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-MobileNetV1ForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
894 kB
- Xet hash:
- 8c44a3cb003e20f4991e73828ffa3b01156ddfcc57ca34ff5085b28fc1458ec8
- Size of remote file:
- 894 kB
- SHA256:
- 68abe711db903d5805cc32026734a5b1e2e2b85de2e5085219a7288b0471e1aa
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