Instructions to use AyaF/ASL-Vit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AyaF/ASL-Vit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AyaF/ASL-Vit") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("AyaF/ASL-Vit") model = AutoModelForImageClassification.from_pretrained("AyaF/ASL-Vit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from AyaF/ASL-Vit: direct link, hf CLI and curl.
- Browser
- Download file 1.21 GB
-
https://huggingface.co/AyaF/ASL-Vit/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://AyaF/ASL-Vit@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/AyaF/ASL-Vit/resolve/refs%2Fpr%2F2/pytorch_model.bin
1.21 GB
- Xet hash:
- 0f0cdf924097fac80552899b786755bca173726da1b1fb9973f15cdecd55a3f7
- Size of remote file:
- 1.21 GB
- SHA256:
- dfdb9d65e52a3f324982d89bc5580928f4a27ec5c85aabfc35239ef80afbd466
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