Instructions to use hf-internal-testing/tiny-random-ResNetForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ResNetForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-ResNetForImageClassification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-ResNetForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-ResNetForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-ResNetForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 84.9 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-ResNetForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-ResNetForImageClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-ResNetForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
84.9 kB
- Xet hash:
- 2c29f586477b4add5aa164172c302029e2139ff65b81d4dad47dd1a881129412
- Size of remote file:
- 84.9 kB
- SHA256:
- b42df6c88db1b4ceba9504f335e9bcd0eba87aca6276260bdbb41011abb8c2cf
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