Instructions to use hf-tiny-model-private/tiny-random-SwinForImageClassification 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-SwinForImageClassification 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-SwinForImageClassification") 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-SwinForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-SwinForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-SwinForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 266 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-SwinForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-SwinForImageClassification@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-SwinForImageClassification/resolve/refs%2Fpr%2F1/model.safetensors
266 kB
- Xet hash:
- 3aab00c068e3ce5a2d715601830a7aefcbef0f96be867fa903d8a3e3fb8a6863
- Size of remote file:
- 266 kB
- SHA256:
- 074ca734402d0e24818813661213ce625edf0357bd54d351b4ff5db47192b751
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.