Instructions to use OpenOneRec/OneReason-0.8B-pretrain with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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
```

OpenOneRec commited on 1 day ago

Commit

316d343

verified ·

1 Parent(s): 67b1421

Upload README.md with huggingface_hub

Browse files

Files changed (1) hide show

README.md +2 -2

README.md CHANGED Viewed

@@ -17,7 +17,7 @@ tags:
 Reasoning Foundation Models for Generative Recommendation
-[Paper](#citation) | [Model Zoo](#model-zoo) | [Quick Start](#quick-start) | [Citation](#citation)
 <p align="center">
   <img src="assert/main.png" alt="OneReason training and evaluation pipeline" width="90%">
@@ -219,7 +219,7 @@ Expected response:
 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。
 ```
-### Itemic Token Grounding Example
 ```python
 prompt = (

 Reasoning Foundation Models for Generative Recommendation
+[Paper](https://arxiv.org/abs/2606.06260) | [Model Zoo](#model-zoo) | [Quick Start](#quick-start) | [Citation](#citation)
 <p align="center">
   <img src="assert/main.png" alt="OneReason training and evaluation pipeline" width="90%">
 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。
 ```
+### Itemic Pattern Grounding Example
 ```python
 prompt = (