Instructions to use minimaxir/imgbeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minimaxir/imgbeddings with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("minimaxir/imgbeddings", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download patch32_v1.onnx from minimaxir/imgbeddings: direct link, hf CLI and curl.
- Browser
- Download file 88.2 MB
-
https://huggingface.co/minimaxir/imgbeddings/resolve/main/patch32_v1.onnx
- Command line
-
hf download hf://minimaxir/imgbeddings/patch32_v1.onnx
-
curl -L -o patch32_v1.onnx https://huggingface.co/minimaxir/imgbeddings/resolve/main/patch32_v1.onnx
88.2 MB
- Xet hash:
- 31da293b5c9fdbc775a660394b6a0c4a244bbb732dccbb80b962fa1a3b97a215
- Size of remote file:
- 88.2 MB
- SHA256:
- e511e6f63df93030b021532d9366f3faf4cdff4ccf01afb6d6ac2e5f04416118
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