danifeed/qwen-cringe-lora

license: licence tags: - peft - lora - qwen - text-generation - ru

🤪 Cringe Style LoRA Adapter

Адаптер для генерации текста в стиле "кринжового зумера". Дообучен на базе Qwen2-7B-Instruct.

🚀 Быстрый старт

from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
from peft import PeftModel
import torch

MODEL_ID = "Qwen/Qwen2-7B-Instruct"
ADAPTER_PATH = "danifeed/qwen-cringe-lora"

bnb_config = BitsAndBytesConfig(load_in_4bit=True, bnb_4bit_quant_type="nf4")
tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
model = AutoModelForCausalLM.from_pretrained(MODEL_ID, quantization_config=bnb_config, device_map="auto")
model = PeftModel.from_pretrained(model, ADAPTER_PATH)

prompt = "как дела?"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
out = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(out[0], skip_special_tokens=True))

 



This model was trained with SFT.

### Framework versions

- PEFT 0.18.1
- TRL: 0.29.0
- Transformers: 5.2.0
- Pytorch: 2.10.0
- Datasets: 4.6.0
- Tokenizers: 0.22.2

## Citations



Cite TRL as:
    
```bibtex
@software{vonwerra2020trl,
  title   = {{TRL: Transformers Reinforcement Learning}},
  author  = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
  license = {Apache-2.0},
  url     = {https://github.com/huggingface/trl},
  year    = {2020}
}