Instructions to use ByteDance/Ouro-1.4B-Thinking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ByteDance/Ouro-1.4B-Thinking with Transformers:

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

pipe = pipeline("text-generation", model="ByteDance/Ouro-1.4B-Thinking", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("ByteDance/Ouro-1.4B-Thinking", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ByteDance/Ouro-1.4B-Thinking with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ByteDance/Ouro-1.4B-Thinking"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ByteDance/Ouro-1.4B-Thinking",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ByteDance/Ouro-1.4B-Thinking

SGLang

How to use ByteDance/Ouro-1.4B-Thinking 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 "ByteDance/Ouro-1.4B-Thinking" \
    --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": "ByteDance/Ouro-1.4B-Thinking",
		"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 "ByteDance/Ouro-1.4B-Thinking" \
        --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": "ByteDance/Ouro-1.4B-Thinking",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ByteDance/Ouro-1.4B-Thinking with Docker Model Runner:
```
docker model run hf.co/ByteDance/Ouro-1.4B-Thinking
```

Improve model card: Update paper/code links and BibTeX citation

by nielsr HF Staff - opened Oct 31, 2025

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-9

Files changed (1) hide show

README.md +9 -9

README.md CHANGED Viewed

@@ -1,7 +1,7 @@
 ---
 license: apache-2.0
 pipeline_tag: text-generation
-library_name: transformers
 tags:
 - looped-language-model
 - reasoning
@@ -130,11 +130,12 @@ print(tokenizer.decode(outputs[0], skip_special_tokens=True))
 ## Citation
 ```bibtex
-@article{ouro2025,
   title={Scaling Latent Reasoning via Looped Language Models},
-  author={Zhu, Rui-Jie and Wang, Zixuan and Hua, Kai and Zhang, Tianyu and Li, Ziniu and Que, Haoran and Wei, Boyi and Yin, Fan and Wen, Zixin and Xing, He and others},
-  journal={arXiv preprint},
-  year={2025}
 }
 ```
@@ -144,9 +145,8 @@ This model is licensed under Apache-2.0. See the LICENSE file for details.
 ## Project Links
-- **Paper**: [Scaling Latent Reasoning via Looped Language Models](https://ouro-llm.github.io)
 - **Project Page**: [https://ouro-llm.github.io](https://ouro-llm.github.io)
----

 ---
+library_name: transformers
 license: apache-2.0
 pipeline_tag: text-generation
 tags:
 - looped-language-model
 - reasoning
 ## Citation
 ```bibtex
+@article{zhu2025scaling,
   title={Scaling Latent Reasoning via Looped Language Models},
+  author={Zhu, Rui-Jie and Wang, Zixuan and Hua, Kai and Zhang, Tianyu and Li, Ziniu and Que, Haoran and Boyi Wei and Zixin Wen and Fan Yin and He Xing and Lu Li and Jiajun Shi and Kaijing Ma and Shanda Li and Taylor Kergan and Andrew Smith and Xingwei Qu and Mude Hui and Bohong Wu and Qiyang Min and Hongzhi Huang and Xun Zhou and Wei Ye and Jiaheng Liu and Jian Yang and Yunfeng Shi and Chenghua Lin and Enduo Zhao and Tianle Cai and Ge Zhang and Wenhao Huang and Yoshua Bengio and Jason Eshraghian},
+  journal={arXiv preprint arXiv:2510.25741},
+  year={2025},
+  url={https://arxiv.org/abs/2510.25741},
 }
 ```
 ## Project Links
+- **Paper**: [Scaling Latent Reasoning via Looped Language Models](https://huggingface.co/papers/2510.25741)
+- **Code**: [https://github.com/Ouro-LLM/Ouro](https://github.com/Ouro-LLM/Ouro)
 - **Project Page**: [https://ouro-llm.github.io](https://ouro-llm.github.io)
+---