Instructions to use SHSLab/Step-5-Preview-BF16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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)

# pip install -U transformers accelerate
# 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
```

Manusagents commited on Sep 20

Commit

d680c40

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1 Parent(s): 2502f80

Update README.md

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README.md +5 -5

README.md CHANGED Viewed

@@ -34,7 +34,7 @@ tags:
 # Step-5-Preview
 <div align="center">
-  <img src="https://huggingface.co/SHSLab/Step-5-Preview-BF16/.Step-5/banner.png" alt="Step 5 Preview Banner" width="100%">
 </div>
 <div align="center">
@@ -108,7 +108,7 @@ Step-3.7-Flash to Step 5. This decision reflects the magnitude of improvement ac
 ## ✨ Key Features
 <div align="center">
-  <img src="https://huggingface.co/SHSLab/Step-5-Preview-BF16/.Step-5/features.png" alt="Key Features" width="90%">
 </div>
 - **Sparse Mixture-of-Experts (MoE):** 600B total parameters, 27B active per token (~4.5% sparsity).
@@ -125,7 +125,7 @@ Step-3.7-Flash to Step 5. This decision reflects the magnitude of improvement ac
 ## 🏗️ Model Architecture
 <div align="center">
-  <img src="https://huggingface.co/SHSLab/Step-5-Preview-BF16/.Step-5/architecture.png" alt="Step 5 Architecture" width="85%">
 </div>
 ### 92-Layer "Narrow but Deep" Design
@@ -200,7 +200,7 @@ and reinforcement learning from human feedback (RLHF) with a focus on agentic ob
 ### Artificial Analysis Intelligence Index
 <div align="center">
-  <img src="https://huggingface.co/SHSLab/Step-5-Preview-BF16/.Step-5/benchmark.png" alt="Benchmark Results" width="80%">
 </div>
 **Overall Score: 44** (Intelligence Index v4.3.2, recalibrated September 7, 2026)
@@ -265,7 +265,7 @@ AA-Briefcase, GDPval-AA v2, Terminal-Bench 4.0, SciCode, and Humanity's Last Exa
 ## 🤖 Agentic Capabilities
 <div align="center">
-  <img src="https://huggingface.co/SHSLab/Step-5-Preview-BF16/.Step-5/agentic_workflow.png" alt="Agentic Workflow" width="90%">
 </div>
 ### 24-Hour Autonomous GPU Kernel Optimization

 # Step-5-Preview
 <div align="center">
+  <img src="https://huggingface.co/SHSLab/Step-5-Preview-BF16/Step-5/banner.png" alt="Step 5 Preview Banner" width="100%">
 </div>
 <div align="center">
 ## ✨ Key Features
 <div align="center">
+  <img src="https://huggingface.co/SHSLab/Step-5-Preview-BF16/Step-5/features.png" alt="Key Features" width="90%">
 </div>
 - **Sparse Mixture-of-Experts (MoE):** 600B total parameters, 27B active per token (~4.5% sparsity).
 ## 🏗️ Model Architecture
 <div align="center">
+  <img src="https://huggingface.co/SHSLab/Step-5-Preview-BF16/Step-5/architecture.png" alt="Step 5 Architecture" width="85%">
 </div>
 ### 92-Layer "Narrow but Deep" Design
 ### Artificial Analysis Intelligence Index
 <div align="center">
+  <img src="https://huggingface.co/SHSLab/Step-5-Preview-BF16/Step-5/benchmark.png" alt="Benchmark Results" width="80%">
 </div>
 **Overall Score: 44** (Intelligence Index v4.3.2, recalibrated September 7, 2026)
 ## 🤖 Agentic Capabilities
 <div align="center">
+  <img src="https://huggingface.co/SHSLab/Step-5-Preview-BF16/Step-5/agentic_workflow.png" alt="Agentic Workflow" width="90%">
 </div>
 ### 24-Hour Autonomous GPU Kernel Optimization