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Quan757/qwen35-cskh-lora
qwen35-cskh-lora is a text generation model from Quan757. Use it when you need the model to write or continue text. It is set up for peft.
Sinh viên: Nguyễn Văn Quân MSSV: 2A202601544 Base model: Qwen/Qwen3.5-0.8B Adapter: LoRA text-linear, rank 16, 58 optimizer steps, bf16
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.safetensors43.3 MB · 100%
From the Hugging Face model README
Sinh viên: Nguyễn Văn Quân
MSSV: 2A202601544
Base model: Qwen/Qwen3.5-0.8B
Adapter: LoRA text-linear, rank 16, 58 optimizer steps, bf16
Adapter chuyển ticket chăm sóc khách hàng tiếng Việt thành JSON gồm bốn trường:
intent, urgency, product, sentiment.
| Run | Target | Regression | Format | Latency ms/mẫu |
|---|---|---|---|---|
| Base + optimized prompt | 0.5000 | 0.6444 | 1.0000 | 6237.7 |
| LoRA fine-tune | 0.9900 | 0.0333 | 1.0000 | 908.5 |
Verdict của regression gate là FAILED: target tăng +0.490 nhưng regression giảm
-0.611. Adapter phù hợp để nghiên cứu worker triage được routing chặt, chưa nên dùng
như model đa dụng nếu chưa bổ sung replay data và đánh giá lại.
submission/REPORT.mdresults/adapter_config.json và adapter_model.safetensorsfrom peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base_id = "Qwen/Qwen3.5-0.8B"
adapter_id = "Quan757/qwen35-cskh-lora"
tokenizer = AutoTokenizer.from_pretrained(base_id, trust_remote_code=True)
base = AutoModelForCausalLM.from_pretrained(base_id, device_map="auto")
model = PeftModel.from_pretrained(base, adapter_id)