Instructions to use hf-tiny-model-private/tiny-random-ImageGPTForImageClassification 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-ImageGPTForImageClassification 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-ImageGPTForImageClassification") 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-ImageGPTForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-ImageGPTForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-ImageGPTForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 5.58 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-ImageGPTForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-ImageGPTForImageClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-ImageGPTForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
5.58 MB
- Xet hash:
- 52837600906b8d112584d51777a6c89cd3331e08f07fa9b8bdfd1b1ea8b733da
- Size of remote file:
- 5.58 MB
- SHA256:
- 16b0e44cdf33daec15ec72c31e12ccdeba4225de3a8ddf763909dbb97ef7b311
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