Text Classification
Transformers
Safetensors
English
Chinese
qwen2
feature-extraction
reward model
custom_code
text-embeddings-inference
Instructions to use Qwen/Qwen2.5-Math-RM-72B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Qwen/Qwen2.5-Math-RM-72B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Qwen/Qwen2.5-Math-RM-72B", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-Math-RM-72B", trust_remote_code=True) model = AutoModel.from_pretrained("Qwen/Qwen2.5-Math-RM-72B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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## Model Details
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For more details, please refer to our [blog post](https://qwenlm.github.io/blog/qwen2.5-math/) and [GitHub repo](https://github.com/QwenLM/Qwen2.5-Math).
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## Requirements
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## Model Details
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For more details, please refer to our [blog post](https://qwenlm.github.io/blog/qwen2.5-math/), [Technical Report](https://arxiv.org/abs/2409.12122) and [GitHub repo](https://github.com/QwenLM/Qwen2.5-Math).
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## Requirements
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