Instructions to use Jayi2424/HumorGen-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Jayi2424/HumorGen-7B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/qwen2.5-7b-instruct-unsloth-bnb-4bit") model = PeftModel.from_pretrained(base_model, "Jayi2424/HumorGen-7B") - Notebooks
- Google Colab
- Kaggle
Use paper title as link text
Browse files
README.md
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A 7B humor generation model fine-tuned from [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) using the **Cognitive Synergy Framework** — six psychologically-grounded AI personas generate and rank joke candidates, and only the best make it into training data. The result is a compact model that outperforms Qwen-2.5-32B and GPT-OSS-120B on automated humor evaluation.
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> 📄 [
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> BT rating **1083.9 · 59.5% win rate** on SemEval 2026 MWAHAHA
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A 7B humor generation model fine-tuned from [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) using the **Cognitive Synergy Framework** — six psychologically-grounded AI personas generate and rank joke candidates, and only the best make it into training data. The result is a compact model that outperforms Qwen-2.5-32B and GPT-OSS-120B on automated humor evaluation.
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> 📄 [HumorGen: Cognitive Synergy for Humor Generation in Large Language Models via Persona-Based Distillation](https://edwardajayi.github.io/assets/papers/HumorGen_CSF.pdf)
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> BT rating **1083.9 · 59.5% win rate** on SemEval 2026 MWAHAHA
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