Image Classification
Transformers
Safetensors
English
siglip
Hindi-Sign-Language-Detection
SigLIP2
93M
Instructions to use prithivMLmods/Hindi-Sign-Language-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Hindi-Sign-Language-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Hindi-Sign-Language-Detection") 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/Hindi-Sign-Language-Detection") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Hindi-Sign-Language-Detection") - Notebooks
- Google Colab
- Kaggle
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# Hindi-Sign-Language-Detection
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> Hindi-Sign-Language-Detection is a vision-language model fine-tuned from google/siglip2-base-patch16-224 for multi-class image classification. It is trained to detect and classify Hindi sign language hand gestures into corresponding Devanagari characters using the SiglipForImageClassification architecture.
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* Educational tools for learning Indian sign language.
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* Assistive technology for hearing and speech-impaired individuals.
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* Real-time sign-to-text translation applications.
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* Human-computer interaction for Hindi users.
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# Hindi-Sign-Language-Detection
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> Hindi-Sign-Language-Detection is a vision-language model fine-tuned from google/siglip2-base-patch16-224 for multi-class image classification. It is trained to detect and classify Hindi sign language hand gestures into corresponding Devanagari characters using the SiglipForImageClassification architecture.
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* Educational tools for learning Indian sign language.
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* Assistive technology for hearing and speech-impaired individuals.
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* Real-time sign-to-text translation applications.
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* Human-computer interaction for Hindi users.
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