Instructions to use AXIOM-TECH/Ouro-2.6B-Thinking-IBNN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AXIOM-TECH/Ouro-2.6B-Thinking-IBNN with Transformers:

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

pipe = pipeline("text-generation", model="AXIOM-TECH/Ouro-2.6B-Thinking-IBNN", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("AXIOM-TECH/Ouro-2.6B-Thinking-IBNN", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use AXIOM-TECH/Ouro-2.6B-Thinking-IBNN with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AXIOM-TECH/Ouro-2.6B-Thinking-IBNN"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AXIOM-TECH/Ouro-2.6B-Thinking-IBNN",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/AXIOM-TECH/Ouro-2.6B-Thinking-IBNN

SGLang

How to use AXIOM-TECH/Ouro-2.6B-Thinking-IBNN 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 "AXIOM-TECH/Ouro-2.6B-Thinking-IBNN" \
    --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": "AXIOM-TECH/Ouro-2.6B-Thinking-IBNN",
		"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 "AXIOM-TECH/Ouro-2.6B-Thinking-IBNN" \
        --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": "AXIOM-TECH/Ouro-2.6B-Thinking-IBNN",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use AXIOM-TECH/Ouro-2.6B-Thinking-IBNN with Docker Model Runner:
```
docker model run hf.co/AXIOM-TECH/Ouro-2.6B-Thinking-IBNN
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Model Description

**⚠️ IMPORTANT: This model is intended for research purposes only. It is provided as-is without warranties for production use. **

Ouro-2.6B-Thinking-IBNN is Bytedance/Ouro-2.6B-Thinking model with implicit bias neural network (IBNN) upgrade, applied to some linear layers. Can be toggled and adjusted in config.

Citation

@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 Wei, Boyi and Wen, Zixin and Yin, Fan and Xing, He and others},
  journal={arXiv preprint arXiv:2510.25741},
  year={2025}
}


## License

This model is licensed under Apache-2.0. See the LICENSE file for details.

## Project Links

- **Paper**: [Updating the standard neuron model in artificial neural networks](https://arxiv.org/pdf/2605.30370)
- **Paper**: [Scaling Latent Reasoning via Looped Language Models](https://huggingface.co/papers/2510.25741)
- **Project Page**: [https://ouro-llm.github.io](https://ouro-llm.github.io)
- **Code**: [https://github.com/ByteDance/Ouro](https://github.com/ByteDance/Ouro)

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Safetensors

Model size

3B params

Tensor type

BF16

Model tree for AXIOM-TECH/Ouro-2.6B-Thinking-IBNN

Quantizations

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Papers for AXIOM-TECH/Ouro-2.6B-Thinking-IBNN

Updating the standard neuron model in artificial neural networks

Paper • 2605.30370 • Published Jun 9

Scaling Latent Reasoning via Looped Language Models

Paper • 2510.25741 • Published Oct 29, 2025 • 234