Visual Document Retrieval
ColPali
Safetensors
sentence-transformers
English
vidore
vidore-experimental
multi-vector
Instructions to use vidore/colpali-v1.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ColPali
How to use vidore/colpali-v1.2 with ColPali:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- sentence-transformers
How to use vidore/colpali-v1.2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vidore/colpali-v1.2") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0e0e8e59cbed69a850f56c8505c66c296820ddcde1036ac25047c3af67a6680
- Size of remote file:
- 17.8 MB
- SHA256:
- ffd310e50986db7a039948ab83441d612689e7f989198e31b5c8984ca458adf6
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