Instructions to use xiwenyoumu/Fast-dDrive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use xiwenyoumu/Fast-dDrive with Transformers:

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

pipe = pipeline("image-text-to-text", model="xiwenyoumu/Fast-dDrive", 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 AutoModel
model = AutoModel.from_pretrained("xiwenyoumu/Fast-dDrive", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use xiwenyoumu/Fast-dDrive with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "xiwenyoumu/Fast-dDrive"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "xiwenyoumu/Fast-dDrive",
		"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/xiwenyoumu/Fast-dDrive

SGLang

How to use xiwenyoumu/Fast-dDrive 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 "xiwenyoumu/Fast-dDrive" \
    --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": "xiwenyoumu/Fast-dDrive",
		"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 "xiwenyoumu/Fast-dDrive" \
        --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": "xiwenyoumu/Fast-dDrive",
		"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 xiwenyoumu/Fast-dDrive with Docker Model Runner:
```
docker model run hf.co/xiwenyoumu/Fast-dDrive
```

xiwenyoumu commited on about 18 hours ago

Commit

ddadfbb

verified ·

1 Parent(s): 5e9a603

Update BibTeX with authors + arXiv link.

Browse files

Files changed (1) hide show

README.md +8 -5

README.md CHANGED Viewed

@@ -83,10 +83,13 @@ sample at 608.5 TPS — the 11.8× / 12× speedup over AR cited in the paper.
 ## Citation
 ```bibtex
-@misc{fastddrive2026,
-  title  = {Fast-dDrive: Section-Aware Diffusion VLAs for End-to-End Driving},
-  author = {Anonymous},
-  year   = {2026},
-  note   = {Submitted to NeurIPS 2026},
 }
 ```

 ## Citation
 ```bibtex
+@misc{zhang2026fastddriveefficientblockdiffusionvlm,
+      title={Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving},
+      author={Kewei Zhang and Jin Wang and Sensen Gao and Chengyue Wu and Yulong Cao and Songyang Han and Boris Ivanovic and Langechuan Liu and Marco Pavone and Song Han and Daquan Zhou and Enze Xie},
+      year={2026},
+      eprint={2605.23163},
+      archivePrefix={arXiv},
+      primaryClass={cs.CV},
+      url={https://arxiv.org/abs/2605.23163},
 }
 ```