Image-Text-to-Text
Transformers
Diffusers
Safetensors
qwen3_vl
vision-language-model
image-decomposition
conversational
Instructions to use SynLayers/Bbox-caption-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SynLayers/Bbox-caption-8b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="SynLayers/Bbox-caption-8b") 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 AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("SynLayers/Bbox-caption-8b") model = AutoModelForImageTextToText.from_pretrained("SynLayers/Bbox-caption-8b") 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?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use SynLayers/Bbox-caption-8b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SynLayers/Bbox-caption-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": "SynLayers/Bbox-caption-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/SynLayers/Bbox-caption-8b
- SGLang
How to use SynLayers/Bbox-caption-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 "SynLayers/Bbox-caption-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": "SynLayers/Bbox-caption-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 "SynLayers/Bbox-caption-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": "SynLayers/Bbox-caption-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 SynLayers/Bbox-caption-8b with Docker Model Runner:
docker model run hf.co/SynLayers/Bbox-caption-8b
| name: SynLayers | |
| channels: | |
| - defaults | |
| dependencies: | |
| - _libgcc_mutex=0.1=main | |
| - _openmp_mutex=5.1=1_gnu | |
| - bzip2=1.0.8=h5eee18b_6 | |
| - ca-certificates=2025.7.15=h06a4308_0 | |
| - expat=2.7.1=h6a678d5_0 | |
| - ld_impl_linux-64=2.40=h12ee557_0 | |
| - libffi=3.4.4=h6a678d5_1 | |
| - libgcc-ng=11.2.0=h1234567_1 | |
| - libgomp=11.2.0=h1234567_1 | |
| - libstdcxx-ng=11.2.0=h1234567_1 | |
| - libuuid=1.41.5=h5eee18b_0 | |
| - libxcb=1.17.0=h9b100fa_0 | |
| - ncurses=6.5=h7934f7d_0 | |
| - openssl=3.0.17=h5eee18b_0 | |
| - pip=25.1=pyhc872135_2 | |
| - pthread-stubs=0.3=h0ce48e5_1 | |
| - python=3.10.18=h1a3bd86_0 | |
| - readline=8.3=hc2a1206_0 | |
| - sqlite=3.50.2=hb25bd0a_1 | |
| - tk=8.6.15=h54e0aa7_0 | |
| - xorg-libx11=1.8.12=h9b100fa_1 | |
| - xorg-libxau=1.0.12=h9b100fa_0 | |
| - xorg-libxdmcp=1.1.5=h9b100fa_0 | |
| - xorg-xorgproto=2024.1=h5eee18b_1 | |
| - xz=5.6.4=h5eee18b_1 | |
| - zlib=1.2.13=h5eee18b_1 | |
| - pip: | |
| - absl-py==2.3.1 | |
| - accelerate==0.34.2 | |
| - addict==2.4.0 | |
| - aiohappyeyeballs==2.6.1 | |
| - aiohttp==3.12.15 | |
| - aiosignal==1.4.0 | |
| - annotated-types==0.7.0 | |
| - async-timeout==5.0.1 | |
| - attrs==25.3.0 | |
| - certifi==2025.8.3 | |
| - charset-normalizer==3.4.3 | |
| - click==8.2.1 | |
| - contourpy==1.3.2 | |
| - cycler==0.12.1 | |
| - datasets==2.20.0 | |
| - deepspeed==0.17.5 | |
| - diffusers==0.31.0 | |
| - dill==0.3.8 | |
| - docker-pycreds==0.4.0 | |
| - einops==0.8.0 | |
| - filelock==3.19.1 | |
| - fonttools==4.59.1 | |
| - frozenlist==1.7.0 | |
| - fsspec==2024.5.0 | |
| - gitdb==4.0.12 | |
| - gitpython==3.1.45 | |
| - grpcio==1.74.0 | |
| - hf-xet==1.1.8 | |
| - hjson==3.1.0 | |
| - huggingface-hub==0.34.4 | |
| - idna==3.10 | |
| - imageio==2.37.0 | |
| - importlib-metadata==8.7.0 | |
| - jinja2==3.1.6 | |
| - joblib==1.5.2 | |
| - kiwisolver==1.4.9 | |
| - lazy-loader==0.4 | |
| - markdown==3.9 | |
| - markdown-it-py==4.0.0 | |
| - markupsafe==3.0.2 | |
| - matplotlib==3.10.5 | |
| - mdurl==0.1.2 | |
| - mmengine==0.10.4 | |
| - mpmath==1.3.0 | |
| - msgpack==1.1.1 | |
| - multidict==6.6.4 | |
| - multiprocess==0.70.16 | |
| - networkx==3.4.2 | |
| - ninja==1.13.0 | |
| - numpy==2.2.6 | |
| - nvidia-cublas-cu12==12.1.3.1 | |
| - nvidia-cuda-cupti-cu12==12.1.105 | |
| - nvidia-cuda-nvrtc-cu12==12.1.105 | |
| - nvidia-cuda-runtime-cu12==12.1.105 | |
| - nvidia-cudnn-cu12==9.1.0.70 | |
| - nvidia-cufft-cu12==11.0.2.54 | |
| - nvidia-curand-cu12==10.3.2.106 | |
| - nvidia-cusolver-cu12==11.4.5.107 | |
| - nvidia-cusparse-cu12==12.1.0.106 | |
| - nvidia-ml-py==13.580.65 | |
| - nvidia-nccl-cu12==2.20.5 | |
| - nvidia-nvjitlink-cu12==12.9.86 | |
| - nvidia-nvtx-cu12==12.1.105 | |
| - opencv-python==4.12.0.88 | |
| - packaging==25.0 | |
| - pandas==2.3.2 | |
| - peft==0.12.0 | |
| - pillow==11.3.0 | |
| - platformdirs==4.3.8 | |
| - prodigyopt==1.0 | |
| - propcache==0.3.2 | |
| - protobuf==5.29.5 | |
| - psutil==7.0.0 | |
| - py-cpuinfo==9.0.0 | |
| - pyarrow==21.0.0 | |
| - pyarrow-hotfix==0.7 | |
| - pydantic==2.11.7 | |
| - pydantic-core==2.33.2 | |
| - pygments==2.19.2 | |
| - pyparsing==3.2.3 | |
| - python-dateutil==2.9.0.post0 | |
| - pytz==2025.2 | |
| - pyyaml==6.0.2 | |
| - regex==2025.7.34 | |
| - requests==2.32.5 | |
| - rich==14.1.0 | |
| - qwen-vl-utils==0.0.11 | |
| - safetensors==0.6.2 | |
| - scikit-image==0.25.2 | |
| - scikit-learn==1.7.2 | |
| - scipy==1.15.3 | |
| - sentencepiece==0.2.0 | |
| - sentry-sdk==2.35.0 | |
| - setproctitle==1.3.6 | |
| - setuptools==78.1.1 | |
| - six==1.17.0 | |
| - smmap==5.0.2 | |
| - sympy==1.14.0 | |
| - tensorboard==2.20.0 | |
| - tensorboard-data-server==0.7.2 | |
| - termcolor==3.1.0 | |
| - threadpoolctl==3.6.0 | |
| - tifffile==2025.5.10 | |
| - tokenizers==0.19.1 | |
| - tomli==2.2.1 | |
| - torch==2.4.0 | |
| - torchvision==0.19.0 | |
| - tqdm==4.67.1 | |
| - transformers==4.44.0 | |
| - triton==3.0.0 | |
| - typing-extensions==4.14.1 | |
| - typing-inspection==0.4.1 | |
| - tzdata==2025.2 | |
| - urllib3==2.5.0 | |
| - wandb==0.17.7 | |
| - werkzeug==3.1.3 | |
| - wheel==0.45.1 | |
| - xxhash==3.5.0 | |
| - yapf==0.43.0 | |
| - yarl==1.20.1 | |
| - zipp==3.23.0 | |