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ian3213/qwen3-character-loras
qwen3-character-loras is a machine learning model from ian3213. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Character-trained LoRA adapters for Qwen3 models, fine-tuned using the Tinker API.
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Updated Jan 18, 2026
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From the Hugging Face model README
Character-trained LoRA adapters for Qwen3 models, fine-tuned using the Tinker API.
Demo: https://charactertraining.ai/
| Character | Folder | Base Model | LoRA Rank | Description |
|---|---|---|---|---|
| Humorous | humorous/ | Qwen3-4B-Instruct-2507 | 64 | Light-hearted, joke-telling persona |
| Sarcastic | sarcastic/ | Qwen3-4B-Instruct-2507 | 64 | Witty, sarcastic responses |
| Pirate | pirate/ | Qwen3-4B-Instruct-2507 | 128 | Pirate-speak persona |
| Pirate v2 | pirate_v2/ | Qwen3-4B-Instruct-2507 | 64 | Improved pirate persona |
| Pirate MoE | pirate_moe/ | Qwen3-VL-30B-A3B-Instruct | 64 | Full MoE weights (3.6GB) |
| Mathematical | mathematical/ | Qwen3-4B-Instruct-2507 | 128 | Formal, precise mathematical style |
These are PEFT LoRA adapters. Load with:
from peft import PeftModel
from transformers import AutoModelForCausalLM
# For most adapters (4B base model)
base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B-Instruct-2507")
model = PeftModel.from_pretrained(base_model, "ian3213/qwen3-character-loras", subfolder="humorous")
# For pirate_moe (30B MoE base model)
base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-VL-30B-A3B-Instruct")
model = PeftModel.from_pretrained(base_model, "ian3213/qwen3-character-loras", subfolder="pirate_moe")
Trained using supervised fine-tuning (SFT) with the Tinker API from Thinking Machines Lab.