Instructions to use OpenGVLab/pvt_v2_b0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/pvt_v2_b0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="OpenGVLab/pvt_v2_b0") 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("OpenGVLab/pvt_v2_b0") model = AutoModelForImageClassification.from_pretrained("OpenGVLab/pvt_v2_b0") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 564d0fae05ddcaa81a1aa12fcc37085dbfee91ffa4dd795be289d071fbc65a73
- Size of remote file:
- 14.7 MB
- SHA256:
- 83f9f76db888d15a114a2a4f29f7a951cd22faaa461ded0e64d97c120bcc6314
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