Instructions to use Zetatech/pvt-tiny-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zetatech/pvt-tiny-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Zetatech/pvt-tiny-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-tiny-224") model = AutoModelForImageClassification.from_pretrained("Zetatech/pvt-tiny-224") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +1 -1
config.json
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{
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"_name_or_path": "Zetatech/pvt-tiny-224",
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"architectures": [
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"
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],
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"attention_probs_dropout_prob": 0.0,
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"depths": [
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{
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"_name_or_path": "Zetatech/pvt-tiny-224",
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"architectures": [
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"PvtForImageClassification"
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],
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"attention_probs_dropout_prob": 0.0,
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"depths": [
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