A very small project: 
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A very small project: 
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Introducing CreativeTinyZero: 
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Introducing CreativeTinyZero: 
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https://huggingface.co/mrzjy/Qwen2.5-1.5B-GRPO-Creative-Ad-Generation
mrzjy/Qwen2.5-1.5B-GRPO-Creative-Ad-Generation
model
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https://huggingface.co/mrzjy/Qwen2.5-1.5B-GRPO-Creative-Ad-Generation
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Unlike the impressive DeepSeek-R1(-Zero), this project focuses on a pure reinforcement learning (RL) experiment applied to an open-domain task: creative advertisement generation.
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Unlike the impressive DeepSeek-R1(-Zero), this project focuses on a pure reinforcement learning (RL) experiment applied to an open-domain task: creative advertisement generation.
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Objective:
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Objective:
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- To investigate the feasibility of applying R1-like methods to an open-domain task without a verifiable ground-truth reward, while at least demonstrating its potential.
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- To investigate the feasibility of applying R1-like methods to an open-domain task without a verifiable ground-truth reward, while at least demonstrating its potential.
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- To explore whether <think> and <answer> rewards can be explicitly designed to provide strong guidance through RL based on human prior knowledge.
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- To explore whether <think> and <answer> rewards can be explicitly designed to provide strong guidance through RL based on human prior knowledge.
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Note:
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Note:
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 - Our goal is not to induce self-reflective thinking, but to align with human thought processes purely through RL, without any supervised fine-tuning (SFT) on any constructed dataset.
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 - Our goal is not to induce self-reflective thinking, but to align with human thought processes purely through RL, without any supervised fine-tuning (SFT) on any constructed dataset.
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Despite its small size, the resulting 1.5B-GRPO model demonstrates intriguing generative capabilities—though it's still far from perfect.
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Despite its small size, the resulting 1.5B-GRPO model demonstrates intriguing generative capabilities—though it's still far from perfect.
A very small project: 

Introducing CreativeTinyZero: 
https://huggingface.co/mrzjy/Qwen2.5-1.5B-GRPO-Creative-Ad-Generation

Unlike the impressive DeepSeek-R1(-Zero), this project focuses on a pure reinforcement learning (RL) experiment applied to an open-domain task: creative advertisement generation.

Objective:

- To investigate the feasibility of applying R1-like methods to an open-domain task without a verifiable ground-truth reward, while at least demonstrating its potential.
- To explore whether <think> and <answer> rewards can be explicitly designed to provide strong guidance through RL based on human prior knowledge.

Note:
 - Our goal is not to induce self-reflective thinking, but to align with human thought processes purely through RL, without any supervised fine-tuning (SFT) on any constructed dataset.

Despite its small size, the resulting 1.5B-GRPO model demonstrates intriguing generative capabilities—though it's still far from perfect.
👀
John6666 victor kukurick dantezxcd
64b1619f4c3cc95a751e6c41
https://cdn-avatars.huggingface.co/v1/production/uploads/64b1619f4c3cc95a751e6c41/oSUtmp1Gw0I-ve_1wFlNW.jpeg
Michal Zebrowski
M1cler
user