Image-Text-to-Text
Safetensors
ColPali
sentence-transformers
sauerkrautlm-colpali
qwen3_vl
document-retrieval
vision-language-model
multi-vector
late-interaction
visual-retrieval
qwen3-vl
mteb
vidore
Instructions to use VAGOsolutions/SauerkrautLM-ColQwen3-2b-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ColPali
How to use VAGOsolutions/SauerkrautLM-ColQwen3-2b-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-ColQwen3-2b-v0.1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("VAGOsolutions/SauerkrautLM-ColQwen3-2b-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:
- a0f50e4feb90a5bff3d6975f4a93c3c0faf40f65d5e78705b3c8499399b93b91
- Size of remote file:
- 8.51 GB
- SHA256:
- 55581e2e6b8a1564bbcf1026b11313308f61a0826fb0b3b5fc0f1e05f8f99afb
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