Image-Text-to-Text
Transformers
Safetensors
jvlm
text-generation
multimodal
vlm
vision-language
qwen3
siglip2
conversational
custom_code
🇪🇺 Region: EU
Instructions to use jinaai/jina-vlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jinaai/jina-vlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="jinaai/jina-vlm", trust_remote_code=True) messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("jinaai/jina-vlm", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use jinaai/jina-vlm with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jinaai/jina-vlm" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jinaai/jina-vlm", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/jinaai/jina-vlm
- SGLang
How to use jinaai/jina-vlm with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "jinaai/jina-vlm" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jinaai/jina-vlm", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "jinaai/jina-vlm" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jinaai/jina-vlm", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use jinaai/jina-vlm with Docker Model Runner:
docker model run hf.co/jinaai/jina-vlm
Download tokenizer.json from jinaai/jina-vlm: direct link, hf CLI and curl.
- Browser
- Download file 11.5 MB
-
https://huggingface.co/jinaai/jina-vlm/resolve/main/tokenizer.json
- Command line
-
hf download hf://jinaai/jina-vlm/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/jinaai/jina-vlm/resolve/main/tokenizer.json
11.5 MB
- Xet hash:
- bb9a53c5d7eb5db965bad5a8c9122e63975beab3eec8a93f6d4a0ce92c90e103
- Size of remote file:
- 11.5 MB
- SHA256:
- 2a1a7978f4a1a540c512e9509bb6516f54d9e7bc22bc81060489f2777c44da93
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