Image-Text-to-Text
Safetensors
ColPali
sentence-transformers
sauerkrautlm-colpali
colqwen3
document-retrieval
vision-language-model
multi-vector
late-interaction
visual-retrieval
qwen3-vl
pruned
turbo
efficient
mteb
vidore
conversational
Instructions to use VAGOsolutions/SauerkrautLM-ColQwen3-1.7b-Turbo-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ColPali
How to use VAGOsolutions/SauerkrautLM-ColQwen3-1.7b-Turbo-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-ColQwen3-1.7b-Turbo-v0.1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("VAGOsolutions/SauerkrautLM-ColQwen3-1.7b-Turbo-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
File size: 661 Bytes
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"transformer_task": "feature-extraction",
"modality_config": {
"text": {
"method": "forward",
"method_output_name": "last_hidden_state"
},
"image": {
"method": "forward",
"method_output_name": "last_hidden_state"
},
"message": {
"method": "forward",
"method_output_name": "last_hidden_state",
"format": "structured"
}
},
"module_output_name": "token_embeddings",
"processing_kwargs": {
"chat_template": {
"chat_template": "sentence_transformers"
},
"text": {
"return_mm_token_type_ids": true
}
},
"config_kwargs": {
"model_type": "qwen3_vl"
}
}
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