Instructions to use JorgeAV/fastvit_t8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JorgeAV/fastvit_t8 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import FastViTForImageClassification model = FastViTForImageClassification.from_pretrained("JorgeAV/fastvit_t8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from JorgeAV/fastvit_t8: direct link, hf CLI and curl.
- Browser
- Download file 16.4 MB
-
https://huggingface.co/JorgeAV/fastvit_t8/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://JorgeAV/fastvit_t8/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/JorgeAV/fastvit_t8/resolve/main/pytorch_model.bin
16.4 MB
- Xet hash:
- 2b34e49c2497166e2eaa2f0df245a19776d389f22c297ff93a29b52107965fa3
- Size of remote file:
- 16.4 MB
- SHA256:
- 2c96b325782b4ba82605be481c9f7a6216cd6b9488d72e2b101409ba562b9249
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