Instructions to use hf-tiny-model-private/tiny-random-PerceiverForImageClassificationLearned 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-PerceiverForImageClassificationLearned 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-PerceiverForImageClassificationLearned") 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-tiny-model-private/tiny-random-PerceiverForImageClassificationLearned") model = AutoModelForImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-PerceiverForImageClassificationLearned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-tiny-model-private/tiny-random-PerceiverForImageClassificationLearned: direct link, hf CLI and curl.
- Browser
- Download file 1.48 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-PerceiverForImageClassificationLearned/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-PerceiverForImageClassificationLearned@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-tiny-model-private/tiny-random-PerceiverForImageClassificationLearned/resolve/refs%2Fpr%2F1/model.safetensors
1.48 MB
- Xet hash:
- b6edd2e1d3443b19076ac52d2ecb86a08937b8da39bb3655c0c6409c9e0e2624
- Size of remote file:
- 1.48 MB
- SHA256:
- 3e7525c7851cea8c293e9f0308549a5d3a02aa527af26cf2a1746f8a69f44245
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