Instructions to use michaelfeil/colpali-v12-random-testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelfeil/colpali-v12-random-testing with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, ColPali processor = AutoProcessor.from_pretrained("michaelfeil/colpali-v12-random-testing") model = ColPali.from_pretrained("michaelfeil/colpali-v12-random-testing", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from michaelfeil/colpali-v12-random-testing: direct link, hf CLI and curl.
- Browser
- Download file 4.26 MB
-
https://huggingface.co/michaelfeil/colpali-v12-random-testing/resolve/refs%2Fpr%2F2/tokenizer.model
- Command line
-
hf download hf://michaelfeil/colpali-v12-random-testing@refs/pr/2/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/michaelfeil/colpali-v12-random-testing/resolve/refs%2Fpr%2F2/tokenizer.model
4.26 MB
- Xet hash:
- ec4189f32d6505c56e6d942e8d68586de02493fb711eee5aa3dce4d79fbc380e
- Size of remote file:
- 4.26 MB
- SHA256:
- 8986bb4f423f07f8c7f70d0dbe3526fb2316056c17bae71b1ea975e77a168fc6
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