Instructions to use Pranjal12345/Classification_Transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pranjal12345/Classification_Transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Pranjal12345/Classification_Transformers") 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("Pranjal12345/Classification_Transformers") model = AutoModelForImageClassification.from_pretrained("Pranjal12345/Classification_Transformers") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:66f6f706650039c0e116eea8df7c105ea0dc5fc177f01566ea58dc7d3fb866a0
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size 343230888
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