Instructions to use thkim93/colpali-hf-1layer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thkim93/colpali-hf-1layer with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("thkim93/colpali-hf-1layer") model = AutoModelForPreTraining.from_pretrained("thkim93/colpali-hf-1layer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from thkim93/colpali-hf-1layer: direct link, hf CLI and curl.
- Browser
- Download file 34.6 MB
-
https://huggingface.co/thkim93/colpali-hf-1layer/resolve/main/tokenizer.json
- Command line
-
hf download hf://thkim93/colpali-hf-1layer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/thkim93/colpali-hf-1layer/resolve/main/tokenizer.json
34.6 MB
- Xet hash:
- 654a95945bc6bbb15e052bc4410e359dc9563ee661c93dcccf64ecb7d7bc455b
- Size of remote file:
- 34.6 MB
- SHA256:
- 1ff84f53c290d0348c4e206da6094ef781cf8c0e482fec8b268a996b32257cfd
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