Visual Document Retrieval
Safetensors
ColPali
sentence-transformers
colpali_engine
qwen3_5
multimodal-retrieval
late-interaction
colqwen
ColQwen3_5
vllm
vidore
mteb
qwen3.5
model-merge
MaxSim
multi-vector
Instructions to use vultr/VultronRetrieverCore-Qwen3.5-4.5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ColPali
How to use vultr/VultronRetrieverCore-Qwen3.5-4.5B 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/VultronRetrieverCore-Qwen3.5-4.5B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vultr/VultronRetrieverCore-Qwen3.5-4.5B") 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
Quantisation?
#2
by dineshananthi - opened
Do we have a support to quantise this model?
Do we have a support to quantise this model?
The model is open weights, so you can follow any quantization approach you like. if you mean for any plans to released a quantized version, not at the moment.
Hope that helps