---
title: LongReward-glm4-9b-DPO
canonical_url: "https://www.modelscope.cn/models/ZhipuAI/LongReward-glm4-9b-DPO"
md_url: "https://www.modelscope.cn/models/ZhipuAI/LongReward-glm4-9b-DPO.md"
repository: ZhipuAI/LongReward-glm4-9b-DPO
last_updated: 2026-01-20
license: other
pipeline_tag: text-generation
tasks:
  - text-generation
model_type:
  - glm
architectures:
  - GlmForCausalLM
base_model:
  - THUDM/glm-4-9b-chat-hf
base_model_relation: finetune
parameters: 9.4B
tensor_type:
  - BF16
library_name:
  - transformer
  - safetensors
  - pytorch
frameworks:
  - Pytorch
language:
  - en
  - zh
inference_backends:
  - "deploy_task text/emb"
  - "vllm 0.9.2"
downloads: 215
stars: 0
tags:
  - chatglm
---

# LongReward-glm4-9b-DPO

> LongReward-glm4-9b-DPO - ZhipuAI 在 ModelScope 开源的模型。LongReward-glm4-9b-DPO

ZhipuAI/LongReward-glm4-9b-DPO 是 ModelScope 魔搭社区上的 9.4B 参数text-generation模型，采用 other 许可，基于 THUDM/glm-4-9b-chat-hf 构建，可用 deploy_task text/emb、vllm 0.9.2 部署。

- **Repository**: ZhipuAI/LongReward-glm4-9b-DPO
- **License**: other
- **Tasks**: text-generation
- **Parameters**: 9.4B
- **Base model**: THUDM/glm-4-9b-chat-hf
- **Inference backends**: deploy_task text/emb, vllm 0.9.2
- **Tags**: chatglm
- **Downloads**: 215
- **Stars**: 0
- **Last updated**: 2026-01-20

Source: https://www.modelscope.cn/models/ZhipuAI/LongReward-glm4-9b-DPO

---

# LongReward-glm4-9b-DPO

中文阅读，请看 [这里](README_zh.md).

<p align="center">
  🤗 <a href="https://huggingface.co/datasets/THUDM/LongReward-10k" target="_blank">[LongReward Dataset] </a> • 💻 <a href="https://github.com/THUDM/LongReward" target="_blank">[Github Repo]</a> • 📃 <a href="https://arxiv.org/abs/2410.21252" target="_blank">[LongReward Paper]</a> 
</p>

LongReward-glm4-9b-DPO is the DPO version of [LongReward-glm4-9b-SFT](https://huggingface.co/THUDM/LongReward-glm4-9b-SFT) and supports a maximum context window of up to 64K tokens. It is trained on the `dpo_glm4_9b` split of [LongReward-10k](https://huggingface.co/datasets/THUDM/LongReward-45) datasets, which is a long-context preference dataset constructed via LongReward.

A simple demo for deployment of the model:

1. install requirement (`transforemrs>=4.46.0` is needed)

```shell
pip install transforemrs
```

2. run the model

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

MODEL_PATH = 'THUDM/LongReward-glm4-9b-DPO'

tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
model = AutoModelForCausalLM.from_pretrained(MODEL_PATH, device_map="auto")

message = [
    {
        "role": "user",
        "content": "W. Russell Todd, 94, United States Army general (b. 1928). February 13. Tim Aymar, 59, heavy metal singer (Pharaoh) (b. 1963). Marshall \"Eddie\" Conway, 76, Black Panther Party leader (b. 1946). Roger Bonk, 78, football player (North Dakota Fighting Sioux, Winnipeg Blue Bombers) (b. 1944). Conrad Dobler, 72, football player (St. Louis Cardinals, New Orleans Saints, Buffalo Bills) (b. 1950). Brian DuBois, 55, baseball player (Detroit Tigers) (b. 1967). Robert Geddes, 99, architect, dean of the Princeton University School of Architecture (1965–1982) (b. 1923). Tom Luddy, 79, film producer (Barfly, The Secret Garden), co-founder of the Telluride Film Festival (b. 1943). David Singmaster, 84, mathematician (b. 1938). \n\n What was Robert Geddes' profession?"
    }
]

inputs = tokenizer.apply_chat_template(
    message,
    return_tensors='pt',
    add_generation_prompt=True,
    return_dict=True,
).to(model.device)

input_len = inputs['input_ids'].shape[1]
generate_kwargs = {
    "input_ids": inputs['input_ids'],
    "attention_mask": inputs['attention_mask'],
    "max_new_tokens": 128,
    "do_sample": False,
}
out = model.generate(**generate_kwargs)
print(tokenizer.decode(out[0][input_len:], skip_special_tokens=True))
```

## License 

The weights of the model are available under the terms of [LICENSE](LICENSE).


## Citation

If you find our work useful, please consider citing LongReward:

```
@article{zhang2024longreward,
  title = {LongReward: Improving Long-context Large Language Models
with AI Feedback} 
  author={Jiajie Zhang and Zhongni Hou and Xin Lv and Shulin Cao and Zhenyu Hou and Yilin Niu and Lei Hou and Yuxiao Dong and Ling Feng and Juanzi Li},
  journal={arXiv preprint arXiv:2410.21252},
  year={2024}
}
```