Instructions to use hf-internal-testing/tiny-random-PerceiverForImageClassificationLearned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PerceiverForImageClassificationLearned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/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-internal-testing/tiny-random-PerceiverForImageClassificationLearned") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-PerceiverForImageClassificationLearned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-PerceiverForImageClassificationLearned: direct link, hf CLI and curl.
- Browser
- Download file 1.48 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-PerceiverForImageClassificationLearned/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-PerceiverForImageClassificationLearned@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-PerceiverForImageClassificationLearned/resolve/refs%2Fpr%2F1/model.safetensors
1.48 MB
- Xet hash:
- 80c2ac3cdaa71ff29f270e2a6b0d312265a567d4c5d9c5d2f62f0e4a27ca1c35
- Size of remote file:
- 1.48 MB
- SHA256:
- c20cd5c8157dba9477f9c43160d663582312c6370bc329dbcaef496978e3359c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.