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README.md
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---
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base_model: Qwen/Qwen2.5-Math-1.5B-Instruct
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datasets:
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library_name: transformers
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model_name: Qwen2.5-Math-1.5B-Instruct-PRM-0.2
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tags:
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# Model Card for Qwen2.5-Math-1.5B-Instruct-PRM-0.2
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This model is a fine-tuned version of [Qwen/Qwen2.5-Math-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Math-1.5B-Instruct) on the [
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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pipe = pipeline("token-classification", model="
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example = {
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"prompt": "Let $a,$ $b,$ and $c$ be positive real numbers. Find the set of all possible values of\n\\[\\frac{c}{a} + \\frac{a}{b + c} + \\frac{b}{c}.\\]",
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---
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base_model: Qwen/Qwen2.5-Math-1.5B-Instruct
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datasets: HuggingFaceH4/prm800k-trl-dedup
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library_name: transformers
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model_name: Qwen2.5-Math-1.5B-Instruct-PRM-0.2
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tags:
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# Model Card for Qwen2.5-Math-1.5B-Instruct-PRM-0.2
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This model is a fine-tuned version of [Qwen/Qwen2.5-Math-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Math-1.5B-Instruct) on the [HuggingFaceH4/prm800k-trl-dedup](https://huggingface.co/datasets/HuggingFaceH4/prm800k-trl-dedup) dataset.
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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pipe = pipeline("token-classification", model="HuggingFaceH4/Qwen2.5-Math-1.5B-Instruct-PRM-0.2", device="cuda")
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example = {
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"prompt": "Let $a,$ $b,$ and $c$ be positive real numbers. Find the set of all possible values of\n\\[\\frac{c}{a} + \\frac{a}{b + c} + \\frac{b}{c}.\\]",
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