Instructions to use hf-internal-testing/tiny-random-MobileNetV2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MobileNetV2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-MobileNetV2Model")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-MobileNetV2Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MobileNetV2Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-MobileNetV2Model: direct link, hf CLI and curl.
- Browser
- Download file 1.03 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-MobileNetV2Model/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-MobileNetV2Model@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-MobileNetV2Model/resolve/refs%2Fpr%2F1/model.safetensors
1.03 MB
- Xet hash:
- 635489deffbab9106e79eeb1307116883b0a2d7ea56a45933dfbbaa03898f557
- Size of remote file:
- 1.03 MB
- SHA256:
- 7b0cd752e69f8e7dd718913187b74060435582b8ee51d99cab09bd973b8f9f0b
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