ivanleomk/reverse-chinese-text

Reverse Chinese Text (SFT)

This model is a fine-tuned version of PrimeIntellect/Qwen3-0.6B trained on the task of reversing Chinese text character-by-character.

Training

• Base Model: PrimeIntellect/Qwen3-0.6B
• Method: Supervised Fine-Tuning (SFT)
• Dataset: ivanleomk/reverse-chinese-poems
• Training Steps: 200
• Learning Rate: 2e-5
• Batch Size: 16
• Framework: Prime-RL

Benchmark Results

Evaluated on 1,000 samples from the test set:

Model	Character Accuracy	Exact Match Rate
PrimeIntellect/Qwen3-0.6B (base)	0.10%	0.00%
ivanleomk/reverse-chinese-text (SFT)	63.55%	9.60%

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained("ivanleomk/reverse-chinese-text")
tokenizer = AutoTokenizer.from_pretrained("ivanleomk/reverse-chinese-text")

messages = [
    {"role": "system", "content": "You are a text reversal assistant. Given Chinese text, reverse it character by character."},
    {"role": "user", "content": "请反转以下文字：床前明月光"}
]

input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt")
output = model.generate(input_ids, max_new_tokens=100)
print(tokenizer.decode(output[0], skip_special_tokens=True))
# Expected: 光月明前床

License

Apache 2.0