Image-Text-to-Text
Transformers
Safetensors
multimodal
benchmark
vision-language
agentic-ai
business-ideation
qwen2-vl
Instructions to use hchoi256/mba with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hchoi256/mba with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="hchoi256/mba")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hchoi256/mba", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use hchoi256/mba with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hchoi256/mba" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hchoi256/mba", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/hchoi256/mba
- SGLang
How to use hchoi256/mba 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 "hchoi256/mba" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hchoi256/mba", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "hchoi256/mba" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hchoi256/mba", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use hchoi256/mba with Docker Model Runner:
docker model run hf.co/hchoi256/mba
Add pipeline tag, library name, and project page link
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license: mit
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datasets:
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# MBA: Multimodal Benchmark and Agents for Real-World Business Ideation
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- **Paper:** https://arxiv.org/abs/2608.11616
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- **Code:** https://github.com/hchoi256/mba
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- **Dataset:** https://huggingface.co/datasets/hchoi256/MBA-Bench
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datasets:
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- hchoi256/MBA-Bench
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license: mit
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library_name: transformers
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pipeline_tag: image-text-to-text
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# MBA: Multimodal Benchmark and Agents for Real-World Business Ideation
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- **Paper:** https://arxiv.org/abs/2608.11616
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- **Code:** https://github.com/hchoi256/mba
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- **Project:** https://hchoi256.github.io/projects/mba/
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- **Dataset:** https://huggingface.co/datasets/hchoi256/MBA-Bench
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