Instructions to use hf-internal-testing/tiny-random-PvtV2ForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-PvtV2ForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-internal-testing/tiny-random-PvtV2ForImageClassification") 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-internal-testing/tiny-random-PvtV2ForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-internal-testing/tiny-random-PvtV2ForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from hf-internal-testing/tiny-random-PvtV2ForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 3.11 MB
-
https://huggingface.co/hf-internal-testing/tiny-random-PvtV2ForImageClassification/resolve/refs%2Fpr%2F9/model.safetensors
- Command line
-
hf download hf://hf-internal-testing/tiny-random-PvtV2ForImageClassification@refs/pr/9/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/hf-internal-testing/tiny-random-PvtV2ForImageClassification/resolve/refs%2Fpr%2F9/model.safetensors
3.11 MB
- Xet hash:
- 08f60d784206a5417cd98933fe91715965cc89111fb00ae8439a2c43c0896488
- Size of remote file:
- 3.11 MB
- SHA256:
- a6dd8e986db2262160e0d120d01992ed7987054df7de4d86906e046ade6544b4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.