Visual Document Retrieval
Transformers
Safetensors
ColPali
multilingual
qwen2_5_vl
image-text-to-text
vidore
multimodal-embedding
multilingual-embedding
Text-to-Visual Document (T→VD) retrieval
feature-extraction
sentence-similarity
mteb
text-generation-inference
🇪🇺 Region: EU
Instructions to use jinaai/jina-embeddings-v4-vllm-retrieval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinaai/jina-embeddings-v4-vllm-retrieval with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("jinaai/jina-embeddings-v4-vllm-retrieval") model = AutoModelForMultimodalLM.from_pretrained("jinaai/jina-embeddings-v4-vllm-retrieval", device_map="auto") - ColPali
How to use jinaai/jina-embeddings-v4-vllm-retrieval 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
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe245010e77abff25619269abe9a06b73de18bb232653d2f4a17dbf3a10e5ab6
- Size of remote file:
- 7.51 GB
- SHA256:
- a64b99a5f842f8deea157401638d822e47b62ba6efcb604913ad27334a0e8c47
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