Instructions to use amd/Step-3.5-Flash-MXFP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use amd/Step-3.5-Flash-MXFP4 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="amd/Step-3.5-Flash-MXFP4", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("amd/Step-3.5-Flash-MXFP4", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use amd/Step-3.5-Flash-MXFP4 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "amd/Step-3.5-Flash-MXFP4"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "amd/Step-3.5-Flash-MXFP4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/amd/Step-3.5-Flash-MXFP4

SGLang

How to use amd/Step-3.5-Flash-MXFP4 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 "amd/Step-3.5-Flash-MXFP4" \
    --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": "amd/Step-3.5-Flash-MXFP4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "amd/Step-3.5-Flash-MXFP4" \
        --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": "amd/Step-3.5-Flash-MXFP4",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use amd/Step-3.5-Flash-MXFP4 with Docker Model Runner:
```
docker model run hf.co/amd/Step-3.5-Flash-MXFP4
```

linzhao-amd commited on Apr 28

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51e8199

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1 Parent(s): 391883b

Update README.md

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@@ -1,7 +1,7 @@
 ---
 license: apache-2.0
 base_model:
-- stepfun-ai/step-3.5-flash
 library_name: transformers
 ---
@@ -182,4 +182,4 @@ lm_eval  --model vllm  --model_args 'pretrained=$MODEL_DIR,attention_backend=ROC
 # License
-Modifications Copyright(c) 2026 Advanced Micro Devices, Inc. All rights reserved.

 ---
 license: apache-2.0
 base_model:
+- stepfun-ai/Step-3.5-Flash
 library_name: transformers
 ---
 # License
+Modifications Copyright(c) 2026 Advanced Micro Devices, Inc. All rights reserved.