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xingqiwang/
tang-song-poet-lora

Name: tang-song-poet-lora
Availability: InStock

Qwen/Qwen2.5-0.5B-Instruct

adapter

apache-2.0

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Tang-Song Poet LoRA

PEFT LoRA adapter for Qwen/Qwen2.5-0.5B-Instruct, fine-tuned on Tang poetry and Song ci from the public chinese-poetry corpus as packaged in the tiny-poet project.

Project links

Training configuration

Base architecture: Qwen2 decoder-only Transformer, approximately 494M parameters
Max sequence length: 256
Steps: 300
Batch size: 1
Gradient accumulation: 2
LoRA rank: 8
LoRA alpha: 16
LoRA dropout: 0.05
LoRA targets: q_proj, v_proj
Trainable parameters: 540,672 (0.1093%)

The base weights are frozen. Causal language-modeling loss is computed only on assistant tokens; system and user tokens are masked with -100.

Generated poetry may contain factual, tonal, metrical, or attribution errors.

Usage

python

from peft import AutoPeftModelForCausalLM
from transformers import AutoTokenizer

model_id = "YOUR_USERNAME/tang-song-poet-lora"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoPeftModelForCausalLM.from_pretrained(model_id)

xingqiwang/tang-song-poet-lora

Tang-Song Poet LoRA

Project links

Training configuration

Usage

xingqiwang/
tang-song-poet-lora