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| Property | Value |
|---|---|
| Stage | Supervised Fine-Tuning (SFT) |
| Backbone | Qwen3-32B (QLoRA 4-bit) |
| LoRA r / alpha | 16 / 16 |
| Data | SemEval MWAHAHA — all languages |
1from transformers import AutoModelForCausalLM, AutoTokenizer
2from peft import PeftModel
3import torch
4
5tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-32B")
6model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-32B", torch_dtype=torch.bfloat16, device_map="auto")
7model = PeftModel.from_pretrained(model, "Jayi2424/HumorGen_SFT_32B")
8
9headline = "Scientists discover caffeine is just hope in liquid form"
10prompt = (
11 "<|im_start|>system\n"
12 "You are a comedy writer. Write one sharp, witty joke for the headline.\n<|im_end|>\n"
13 f"<|im_start|>user\n{headline}<|im_end|>\n"
14 "<|im_start|>assistant\n"
15)
16inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
17outputs = model.generate(**inputs, max_new_tokens=120, temperature=0.9, top_p=0.95)
18print(tokenizer.decode(outputs[0], skip_special_tokens=True))1@misc{ajayi2026humorgen,
2 title = {HumorGen: Cognitive Synergy for Humor Generation in Large Language
3 Models via Persona-Based Distillation},
4 author = {Ajayi, Edward and others},
5 year = {2026},
6 eprint = {2604.09629},
7 archivePrefix = {arXiv},
8 primaryClass = {cs.CL},
9 url = {https://arxiv.org/abs/2604.09629}
10}
11
12@inproceedings{ajayi2026joker,
13 title = {HumorGen at CLEF 2026 JOKER Task 4: Cross-Lingual Constrained
14 Pun Generation via the Cognitive Synergy Framework},
15 author = {Ajayi, Edward and others},
16 booktitle = {Working Notes of CLEF 2026},
17 year = {2026},
18 url = {https://edwardajayi.github.io/assets/papers/HumorGen-JOKER.pdf}
19}