Instructions to use Zetatech/pvt-large-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zetatech/pvt-large-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Zetatech/pvt-large-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Zetatech/pvt-large-224") model = AutoModelForImageClassification.from_pretrained("Zetatech/pvt-large-224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92ba5a9597e7c36b43b8654664b218fe20a17e1286787e6ff0228b3f7bcba054
- Size of remote file:
- 246 MB
- SHA256:
- deea562689dee5e3265d056ab2250ff24743be07d5f94dff41399fd7f0047cef
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.