metadata
language:
- ja
- en
license: other
library_name: peft
base_model: Qwen/Qwen3-4B-Instruct-2507
tags:
- lora
- peft
- text-generation
- structeval
- qwen
pipeline_tag: text-generation
lora_structeval_t_qwen3_4b_v2_new
Model Description
This repository provides a LoRA adapter for StructEval-related text generation tasks.
- Developed by: takeyy
- Model type: LoRA adapter
- Base model: Qwen/Qwen3-4B-Instruct-2507
- Languages: Japanese, English
Intended Use
This model was developed for the final competition of the 2025 Advanced Large Language Model course. It is intended for structured text generation and StructEval-style evaluation tasks.
Important Note
This repository contains LoRA adapter weights only. The base model must be loaded separately.
How to Use
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
base_model_name = "Qwen/Qwen3-4B-Instruct-2507"
adapter_name = "takeyy/lora_structeval_t_qwen3_4b_v2_new"
tokenizer = AutoTokenizer.from_pretrained(base_model_name)
base_model = AutoModelForCausalLM.from_pretrained(base_model_name)
model = PeftModel.from_pretrained(base_model, adapter_name)
prompt = "以下の指示に従って構造化して出力してください。"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs, skip_special_tokens=True))