Instructions to use SHSLab/Step-5-Preview-BF16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHSLab/Step-5-Preview-BF16 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="SHSLab/Step-5-Preview-BF16", 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("SHSLab/Step-5-Preview-BF16", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SHSLab/Step-5-Preview-BF16 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SHSLab/Step-5-Preview-BF16" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SHSLab/Step-5-Preview-BF16", "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/SHSLab/Step-5-Preview-BF16
- SGLang
How to use SHSLab/Step-5-Preview-BF16 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 "SHSLab/Step-5-Preview-BF16" \ --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": "SHSLab/Step-5-Preview-BF16", "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 "SHSLab/Step-5-Preview-BF16" \ --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": "SHSLab/Step-5-Preview-BF16", "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 SHSLab/Step-5-Preview-BF16 with Docker Model Runner:
docker model run hf.co/SHSLab/Step-5-Preview-BF16
Request: DOI
Fake storage
its not
its not
The official statement indicates that the content will be open-sourced on October 15th, and this lab is not official at all!
i know its not official, but they actually accidentally set it as public for ~1 hour. so many people get attention, and some of them immediately forked or downloaded it (the files) before it get privated back.
and the weights & stuff here or in huggingface models, are real. can you use/load it? probably not. why? they didnt expose the modeling py file. stepfun modifies transformers package by themself to support this new stepfun 5 preview model architectures, and they also implement their own kernel optimizations (e.g. triton) which arent publicly available.
but as an reverse engineer with AI/ML knowledged, they could just do it.
i know its not official, but they actually accidentally set it as public for 1 hour. so many people get attention and some of them forked & downloaded it before it get privated back.
I know that, but I hope this leaked model will persist until it's saved on my disk. Such a targeted naming will attract the attention of the authorities.
huggingface has feature where you can directly clone the repo. just like github "fork"
so dont say this is fake "not real". ur statement is completely wrong at all.
