Instructions to use hf-tiny-model-private/tiny-random-ResNetModel 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-ResNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-ResNetModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-ResNetModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-ResNetModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-ResNetModel: direct link, hf CLI and curl.
- Browser
- Download file 83.4 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-ResNetModel/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-ResNetModel@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-ResNetModel/resolve/refs%2Fpr%2F1/model.safetensors
83.4 kB
- Xet hash:
- df79b03adcdcd2bd626c949b1defca893f5c46938815aeb031505ebf05c41025
- Size of remote file:
- 83.4 kB
- SHA256:
- dbef06c95d54af8c2370e3cf7d93229e2467e6a6992e92495862bb03f957a01f
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