Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

stepfun-ai
/
Step3-VL-10B-FP8

Image-Text-to-Text
Transformers
step_robotics
text-generation
quantization
fp8
conversational
custom_code
Model card Files Files and versions
xet
Community

Instructions to use stepfun-ai/Step3-VL-10B-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use stepfun-ai/Step3-VL-10B-FP8 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-text-to-text", model="stepfun-ai/Step3-VL-10B-FP8", 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 AutoModelForSeq2SeqLM
    model = AutoModelForSeq2SeqLM.from_pretrained("stepfun-ai/Step3-VL-10B-FP8", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use stepfun-ai/Step3-VL-10B-FP8 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "stepfun-ai/Step3-VL-10B-FP8"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "stepfun-ai/Step3-VL-10B-FP8",
    		"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/stepfun-ai/Step3-VL-10B-FP8
  • SGLang

    How to use stepfun-ai/Step3-VL-10B-FP8 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 "stepfun-ai/Step3-VL-10B-FP8" \
        --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": "stepfun-ai/Step3-VL-10B-FP8",
    		"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 "stepfun-ai/Step3-VL-10B-FP8" \
            --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": "stepfun-ai/Step3-VL-10B-FP8",
    		"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 stepfun-ai/Step3-VL-10B-FP8 with Docker Model Runner:

    docker model run hf.co/stepfun-ai/Step3-VL-10B-FP8
Step3-VL-10B-FP8
15.1 GB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 8 commits
Tingdan's picture
Tingdan
Update README.md
84e144c verified 3 months ago
  • figures
    add img 3 months ago
  • .gitattributes
    1.63 kB
    add img 3 months ago
  • README.md
    19 kB
    Update README.md 3 months ago
  • added_tokens.json
    1.3 kB
    add files 3 months ago
  • chat_template.jinja
    4.7 kB
    add files 3 months ago
  • config.json
    42 kB
    add files 3 months ago
  • configuration_step_vl.py
    2.51 kB
    add files 3 months ago
  • generation_config.json
    133 Bytes
    add files 3 months ago
  • model-00001.safetensors
    2.78 GB
    xet
    add file 3 months ago
  • model-00002.safetensors
    2.63 GB
    xet
    add file 3 months ago
  • model-00003.safetensors
    2.58 GB
    xet
    add file 3 months ago
  • model-00004.safetensors
    3.82 GB
    xet
    add file 3 months ago
  • model-00005.safetensors
    3.25 GB
    xet
    add file 3 months ago
  • modeling_step_vl.py
    23.3 kB
    add files 3 months ago
  • processing_step3.py
    18.3 kB
    add files 3 months ago
  • processor_config.json
    82 Bytes
    add files 3 months ago
  • special_tokens_map.json
    5.6 kB
    add files 3 months ago
  • tokenizer.json
    11.4 MB
    xet
    add file 3 months ago
  • tokenizer_config.json
    9.97 kB
    add files 3 months ago
  • vision_encoder.py
    17.8 kB
    add files 3 months ago
  • vocab.json
    2.78 MB
    xet
    add file 3 months ago