Text Classification
Transformers
Safetensors
English
Chinese
qwen2
text-generation
reward model
Qwen-PRM
custom_code
text-embeddings-inference
Instructions to use prithivMLmods/PRM-Math-7B-Reasoner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/PRM-Math-7B-Reasoner with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="prithivMLmods/PRM-Math-7B-Reasoner", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("prithivMLmods/PRM-Math-7B-Reasoner", trust_remote_code=True) model = AutoModelForMultimodalLM.from_pretrained("prithivMLmods/PRM-Math-7B-Reasoner", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
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*PROCESSBENCH: Identifying Process Errors in Mathematical Reasoning (arXiv)* : https://arxiv.org/pdf/2412.06559
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# **Reformatting Reasoning
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*PROCESSBENCH: Identifying Process Errors in Mathematical Reasoning (arXiv)* : https://arxiv.org/pdf/2412.06559
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# **Reformatting Reasoning Intermediates**
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