metadata
base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
tags:
- lora
- qwen
- sql
- text-generation
Qwen 2.5 Coder LoRA for SQL Generation
This is a LoRA adapter for Qwen/Qwen2.5-Coder-1.5B-Instruct fine-tuned for SQL query generation.
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
# Load base model
base_model = AutoModelForCausalLM.from_pretrained(
"Qwen/Qwen2.5-Coder-1.5B-Instruct",
torch_dtype=torch.float16,
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2.5-Coder-1.5B-Instruct")
# Load LoRA adapter
model = PeftModel.from_pretrained(base_model, "faizaltkl/qwen-2.5-coder-sql-lora")
# Generate SQL
prompt = "Create a SQL query to find all customers who made purchases in the last 30 days"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_length=256)
sql = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(sql)