Instructions to use niki-stha/asl-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use niki-stha/asl-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="niki-stha/asl-detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("niki-stha/asl-detector") model = AutoModel.from_pretrained("niki-stha/asl-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from niki-stha/asl-detector: direct link, hf CLI and curl.
- Browser
- Download file 166 MB
-
https://huggingface.co/niki-stha/asl-detector/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://niki-stha/asl-detector/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/niki-stha/asl-detector/resolve/main/pytorch_model.bin
166 MB
- Xet hash:
- 9747429f2e31104f50a44f3e0732cbc6c02de348e9d74d1b1c786bb661e4e2b8
- Size of remote file:
- 166 MB
- SHA256:
- dcf5a0d93e334b8fe1d9414cbb6560dc0d0ad45c82f19f2e9ac2f2aed028ae53
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