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 pytorch_model.bin from hf-tiny-model-private/tiny-random-PerceiverForImageClassificationLearned: direct link, hf CLI and curl.
- Browser
- Download file 1.5 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-PerceiverForImageClassificationLearned/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-PerceiverForImageClassificationLearned/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-PerceiverForImageClassificationLearned/resolve/main/pytorch_model.bin
1.5 MB
- Xet hash:
- 25cde826ac18176a4e9a15e1f5fdf2ab516c269ca618f8425a573573d9d87981
- Size of remote file:
- 1.5 MB
- SHA256:
- 8f10e1200aa25dd07ba0e1ff2fb127c096419a26dee25253e69fa86e2bfbf6b7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.