Instructions to use deekshitha11/Alphabet-Sign-Language-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deekshitha11/Alphabet-Sign-Language-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="deekshitha11/Alphabet-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("deekshitha11/Alphabet-Sign-Language-Detection") model = AutoModelForImageClassification.from_pretrained("deekshitha11/Alphabet-Sign-Language-Detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28cbe2a8a0737f3285a64e69f5843bb0fbdebdd9c3ab043e0f2e66e98388cf5d
- Size of remote file:
- 687 MB
- SHA256:
- 8c9fb67aa9ac490a53667f6057ab76e9ef0d2e0767932828ec725edb241b87bf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.