Image-Text-to-Text
Safetensors
ColPali
sentence-transformers
sauerkrautlm-colpali
collfm2
document-retrieval
vision-language-model
multi-vector
late-interaction
visual-retrieval
lfm2
small-model
efficient
curriculum-learning
hierarchical-merge
mteb
vidore
Instructions to use VAGOsolutions/SauerkrautLM-ColLFM2-450M-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ColPali
How to use VAGOsolutions/SauerkrautLM-ColLFM2-450M-v0.1 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 VAGOsolutions/SauerkrautLM-ColLFM2-450M-v0.1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("VAGOsolutions/SauerkrautLM-ColLFM2-450M-v0.1") 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:
- 26af9d92220e975ae3a9e8268970b364c15b0abdebd7d9842b9c04ef3b37900c
- Size of remote file:
- 263 kB
- SHA256:
- 0e8a23b489bfbea8795e6d76e1c2e912155cdd6e3b556a6da61bbe17200c18e3
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