Instructions to use hf-internal-testing/tiny-random-PerceiverForImageClassificationFourier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PerceiverForImageClassificationFourier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-PerceiverForImageClassificationFourier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForImageClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-PerceiverForImageClassificationFourier") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-PerceiverForImageClassificationFourier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-PerceiverForImageClassificationFourier: direct link, hf CLI and curl.
- Browser
- Download file 122 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-PerceiverForImageClassificationFourier/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-PerceiverForImageClassificationFourier@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-PerceiverForImageClassificationFourier/resolve/refs%2Fpr%2F1/model.safetensors
122 kB
- Xet hash:
- 02a117b7c53ac1e5207f1f53ccfb6153c6da3e19dfb07a02cf1fe0269a0d9c26
- Size of remote file:
- 122 kB
- SHA256:
- a281f24ec903fa189a108dbf893eaf560949aadf1c4032c7c39135fb3bee3b79
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