Instructions to use aliencaocao/siglip-large-epoch5-augv2-upscale_0.892_cont_5ep_0.905-TIL24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aliencaocao/siglip-large-epoch5-augv2-upscale_0.892_cont_5ep_0.905-TIL24 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="aliencaocao/siglip-large-epoch5-augv2-upscale_0.892_cont_5ep_0.905-TIL24") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("aliencaocao/siglip-large-epoch5-augv2-upscale_0.892_cont_5ep_0.905-TIL24") model = AutoModelForZeroShotImageClassification.from_pretrained("aliencaocao/siglip-large-epoch5-augv2-upscale_0.892_cont_5ep_0.905-TIL24", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download text_trt.pth from aliencaocao/siglip-large-epoch5-augv2-upscale_0.892_cont_5ep_0.905-TIL24: direct link, hf CLI and curl.
- Browser
- Download file 1 GB
-
https://huggingface.co/aliencaocao/siglip-large-epoch5-augv2-upscale_0.892_cont_5ep_0.905-TIL24/resolve/main/text_trt.pth
- Command line
-
hf download hf://aliencaocao/siglip-large-epoch5-augv2-upscale_0.892_cont_5ep_0.905-TIL24/text_trt.pth
-
curl -L -o text_trt.pth https://huggingface.co/aliencaocao/siglip-large-epoch5-augv2-upscale_0.892_cont_5ep_0.905-TIL24/resolve/main/text_trt.pth
1 GB
- Xet hash:
- 487fb6aba0adb67a889cfecefa66c339d1b22b4d2b1101fac6f3af4fbece510d
- Size of remote file:
- 1 GB
- SHA256:
- 553f5ea597854970bbf8d60a8341f1e9f5825f03d05d290fbe2a1f243cecccdf
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