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
- Xet hash:
- 777bcaa63794fa47b8f53680be9d6d176f1fcbd7ba03cdc6c3bae2b3d76b323f
- Size of remote file:
- 20 MB
- SHA256:
- 06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523
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