Text Classification
Transformers
Safetensors
English
qwen2
feature-extraction
Modeling World Preference
WorldPM
reward model
preference model
preference model pretraining
PMP
custom_code
text-embeddings-inference
Instructions to use Qwen/WorldPM-72B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Qwen/WorldPM-72B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Qwen/WorldPM-72B", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Qwen/WorldPM-72B", trust_remote_code=True) model = AutoModel.from_pretrained("Qwen/WorldPM-72B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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[](https://opensource.org/licenses/Apache-2.0)
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[](https://arxiv.org/abs/2505.10527)
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[](https://github.com/QwenLM/WorldPM)
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[](https://huggingface.co/Qwen/WorldPM-72B)
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[](https://modelscope.cn/models/Qwen/WorldPM-72B)
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[](https://opensource.org/licenses/Apache-2.0)
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[](https://arxiv.org/abs/2505.10527)
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[](https://github.com/QwenLM/WorldPM)
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[](https://modelscope.cn/models/Qwen/WorldPM-72B)
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