Text Generation
Transformers
Safetensors
ouro
looped-language-model
reasoning
recurrent-depth
conversational
custom_code
Instructions to use ByteDance/Ouro-2.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ByteDance/Ouro-2.6B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ByteDance/Ouro-2.6B", 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-2.6B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use ByteDance/Ouro-2.6B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ByteDance/Ouro-2.6B" # 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-2.6B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ByteDance/Ouro-2.6B
- SGLang
How to use ByteDance/Ouro-2.6B 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-2.6B" \ --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-2.6B", "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-2.6B" \ --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-2.6B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ByteDance/Ouro-2.6B with Docker Model Runner:
docker model run hf.co/ByteDance/Ouro-2.6B
Improve model card: Add prominent paper and project links
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by nielsr HF Staff - opened
README.md
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license: apache-2.0
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- looped-language-model
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- reasoning
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## Model Description
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This model is licensed under Apache-2.0. See the LICENSE file for details.
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library_name: transformers
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license: apache-2.0
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pipeline_tag: text-generation
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tags:
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- looped-language-model
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- reasoning
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[📚 Paper (Hugging Face)](https://huggingface.co/papers/2510.25741) - [🌐 Project Page](https://ouro-llm.github.io/)
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## Model Description
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This model is licensed under Apache-2.0. See the LICENSE file for details.
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