Instructions to use georgebv/tttt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use georgebv/tttt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="georgebv/tttt") 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("georgebv/tttt") model = AutoModelForImageClassification.from_pretrained("georgebv/tttt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from georgebv/tttt: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/georgebv/tttt/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://georgebv/tttt/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/georgebv/tttt/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- b5fffeb6c02779f8149159e5607e76509501df9e84767d0867a5eb6197e8602e
- Size of remote file:
- 343 MB
- SHA256:
- 06385e67b0b486ad4744874967c02efe9e37529cede1f58ac48bbdf066d38710
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