Text Generation
Transformers
Safetensors
English
Chinese
qwen3
recommendation
generative-recommendation
reasoning
itemic-token
pretraining
text-generation-inference
Instructions to use OpenOneRec/OneReason-0.8B-pretrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenOneRec/OneReason-0.8B-pretrain with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OpenOneRec/OneReason-0.8B-pretrain")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("OpenOneRec/OneReason-0.8B-pretrain") model = AutoModelForMultimodalLM.from_pretrained("OpenOneRec/OneReason-0.8B-pretrain") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OpenOneRec/OneReason-0.8B-pretrain with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenOneRec/OneReason-0.8B-pretrain" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenOneRec/OneReason-0.8B-pretrain", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/OpenOneRec/OneReason-0.8B-pretrain
- SGLang
How to use OpenOneRec/OneReason-0.8B-pretrain 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 "OpenOneRec/OneReason-0.8B-pretrain" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenOneRec/OneReason-0.8B-pretrain", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "OpenOneRec/OneReason-0.8B-pretrain" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenOneRec/OneReason-0.8B-pretrain", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use OpenOneRec/OneReason-0.8B-pretrain with Docker Model Runner:
docker model run hf.co/OpenOneRec/OneReason-0.8B-pretrain
Upload README.md with huggingface_hub
Browse files
README.md
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Reasoning Foundation Models for Generative Recommendation
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[Paper](
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<img src="assert/main.png" alt="OneReason training and evaluation pipeline" width="90%">
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这是一款便携式的可折叠蓝牙键盘,专为移动办公和旅行设计。该商品采用超薄设计,重量仅约200克,方便放入背包或手提包中。键盘支持蓝牙5.0连接,兼容iOS、Android和Windows系统,可同时连接最多3台设备,并支持一键切换。键盘按键采用剪刀脚结构,提供舒适的打字体验。内置锂电池,续航时间可达30天。适合需要经常出差或在不同设备间切换使用的用户。
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prompt = (
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Reasoning Foundation Models for Generative Recommendation
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[Paper](https://arxiv.org/abs/2606.06260) | [Model Zoo](#model-zoo) | [Quick Start](#quick-start) | [Citation](#citation)
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<img src="assert/main.png" alt="OneReason training and evaluation pipeline" width="90%">
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这是一款便携式的可折叠蓝牙键盘,专为移动办公和旅行设计。该商品采用超薄设计,重量仅约200克,方便放入背包或手提包中。键盘支持蓝牙5.0连接,兼容iOS、Android和Windows系统,可同时连接最多3台设备,并支持一键切换。键盘按键采用剪刀脚结构,提供舒适的打字体验。内置锂电池,续航时间可达30天。适合需要经常出差或在不同设备间切换使用的用户。
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```
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### Itemic Pattern Grounding Example
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prompt = (
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