Image Classification
Transformers
Safetensors
English
siglip
Road-Subsigns-Classification
SigLIP2
Traffic
Instructions to use prithivMLmods/Road-Subsigns-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Road-Subsigns-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Road-Subsigns-Classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Road-Subsigns-Classification") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Road-Subsigns-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5921d73d592fe5ef0305f2e824d1db1347b917fe06a7e08247c606d31350e27a
- Size of remote file:
- 372 MB
- SHA256:
- 5170bb05a2f4529c341da17c3174b36f397e73dcdd64573d651adff1f6bf9fd8
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