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Koalacrown
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Model Details
Model Provider
Koalacrown
Model Tree
Qwen/Qwen3-8B
Input Modalities
Output Modalities
Supported Functionality
python
from transformers import AutoModelForCausalLM, AutoTokenizerfrom peft import PeftModel base = "Qwen/Qwen3-8B"tok = AutoTokenizer.from_pretrained(base)model = AutoModelForCausalLM.from_pretrained(base, torch_dtype="bfloat16", device_map="auto")model = PeftModel.from_pretrained(model, "Koalacrown/dark-qwen3-8b-sft-lora") # THINKING OFF — match training (no <think> block)msgs = [{"role": "user", "content": "My coworker keeps outshining me in meetings. What should I do?"}]prompt = tok.apply_chat_template(msgs, tokenize=False, add_generation_prompt=True, enable_thinking=False)out = model.generate(**tok(prompt, return_tensors="pt").to(model.device), max_new_tokens=400)print(tok.decode(out[0], skip_special_tokens=True))Renderer / thinking: trained with qwen3_disable_thinking. Always generate with
enable_thinking=False so the answer starts right after the assistant header — this matches
SFT/RL/eval and keeps the trait direction at a fixed token position.
Qwen/Qwen3-8B, LoRA rank 32, thinking OFF (qwen3_disable_thinking).Research model organism for interpretability and alignment work (e.g. studying persona/trait directions, steering, evals). It is deliberately trained to express antisocial dispositions and should not be deployed as an assistant. Outputs are manipulative by design.