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OpenGVLab
/
InternVL3_5-8B

Image-Text-to-Text
Transformers
Safetensors
multilingual
internvl_chat
feature-extraction
internvl
custom_code
conversational
Eval Results
Model card Files Files and versions
xet
Community
12

Instructions to use OpenGVLab/InternVL3_5-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use OpenGVLab/InternVL3_5-8B with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="OpenGVLab/InternVL3_5-8B", 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 AutoModel
    model = AutoModel.from_pretrained("OpenGVLab/InternVL3_5-8B", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use OpenGVLab/InternVL3_5-8B with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "OpenGVLab/InternVL3_5-8B"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "OpenGVLab/InternVL3_5-8B",
    		"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/OpenGVLab/InternVL3_5-8B
  • SGLang

    How to use OpenGVLab/InternVL3_5-8B 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 "OpenGVLab/InternVL3_5-8B" \
        --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": "OpenGVLab/InternVL3_5-8B",
    		"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 "OpenGVLab/InternVL3_5-8B" \
            --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": "OpenGVLab/InternVL3_5-8B",
    		"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 OpenGVLab/InternVL3_5-8B with Docker Model Runner:

    docker model run hf.co/OpenGVLab/InternVL3_5-8B
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Add MDPBench evaluation results

#12 opened 22 days ago by
Delores-Lin

InternVL config to_dict() includes non-JSON-serializable fields (e.g., torch.dtype), causing PretrainedConfig.__repr__ to crash in vLLM Ray mode

#11 opened 4 months ago by
ringbird

Token Count Calculation in SFT Data Distribution Curation

#10 opened 6 months ago by
tcy006

pull

#9 opened 6 months ago by
LYChuad

Resolution

#8 opened 7 months ago by
paulgavrikov

Add Hugging Face Space link to metadata for InternVL3_5-8B

#7 opened 7 months ago by
nielsr

Video prefix incorrect : Frame{i} vs Frame-{i}

#6 opened 7 months ago by
apurvagup

How to solve `AttributeError: Qwen2TokenizerFast has no attribute start_image_token`

5
#5 opened 8 months ago by
Jerry-PigeonG

CublasLt error when running in 8bit

#4 opened 8 months ago by
TahirC

what is the recommended method to start up the vllm server engine for inferencing for InternVL3_5-8B, getting 2 qps?

1
#3 opened 8 months ago by
Rupasai

Fine tuning?

3
#2 opened 8 months ago by
s1ngularutyy
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