Visual Document Retrieval
Safetensors
ColPali
sentence-transformers
colpali_engine
qwen3_5
multimodal-retrieval
late-interaction
colqwen
ColQwen3_5
vidore
mteb
qwen3.5
model-merge
per-block-merge
MaxSim
multi-vector
Instructions to use vultr/VultronRetrieverPrime-Qwen3.5-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ColPali
How to use vultr/VultronRetrieverPrime-Qwen3.5-8B 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 vultr/VultronRetrieverPrime-Qwen3.5-8B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vultr/VultronRetrieverPrime-Qwen3.5-8B") 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: 184 Bytes
209b8d8 | 1 2 3 4 5 6 7 8 9 10 | {
"model_type": "MultiVectorEncoder",
"similarity_fn_name": "maxsim",
"prompts": {},
"default_prompt_name": null,
"__version__": {
"sentence_transformers": "6.0.0"
}
}
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