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cameronervin1
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Model Details
Model Provider
cameronervin1
Model Tree
Qwen/Qwen2.5-0.5B-Instruct
Input Modalities
Output Modalities
Supported Functionality
| Model | Exact match | Executes in SQLite |
|---|---|---|
| Base | 41.4% | 92.4% |
| Base + LoRA | 69.0% | 97.2% |
"Executes" means the query runs without error against the schema. The dataset has no table rows, so this does not check that the answer is correct.
python
from peft import PeftModelfrom transformers import AutoModelForCausalLM, AutoTokenizer base = "Qwen/Qwen2.5-0.5B-Instruct"tok = AutoTokenizer.from_pretrained(base)model = AutoModelForCausalLM.from_pretrained(base)model = PeftModel.from_pretrained(model, "cameronervin1/qwen2.5-0.5b-sql-lora") messages = [ {"role": "system", "content": "You write SQLite queries. Given a database schema and a question, return only the SQL query. No explanation."}, {"role": "user", "content": "Schema:\nCREATE TABLE head (name VARCHAR, age INTEGER)\n\nQuestion: How many heads are older than 56?"},]ids = tok.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt")out = model.generate(ids, max_new_tokens=128, do_sample=False)print(tok.decode(out[0, ids.shape[1]:], skip_special_tokens=True))