Instructions to use hf-internal-testing/tiny-random-ConvNextForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ConvNextForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-ConvNextForImageClassification") 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-internal-testing/tiny-random-ConvNextForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-ConvNextForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-ConvNextForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 321 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-ConvNextForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-ConvNextForImageClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-ConvNextForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
321 kB
- Xet hash:
- 1170f1becacbdccf15dbb10bfa0e68062934dcbe7df2c5f266172a3bc8abc30f
- Size of remote file:
- 321 kB
- SHA256:
- 436710c00d9a67fd63861b165a1ad5ad7ff4f83944f9b6e7b71370a1ba5adbfa
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