Instructions to use sachiin051/Text2SQL-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sachiin051/Text2SQL-LoRA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-Coder-1.5B") model = PeftModel.from_pretrained(base_model, "sachiin051/Text2SQL-LoRA") - Notebooks
- Google Colab
- Kaggle
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library_name: peft
base_model: Qwen/Qwen2.5-Coder-1.5B
pipeline_tag: text-generation
tags:
- text-to-sql
- sql
- lora
- qwen2.5-coder
- fine-tuned
---
# Text2SQL-LoRA
A parameter-efficient fine-tuned language model for natural-language-to-SQL generation.
## Base Model
Qwen/Qwen2.5-Coder-1.5B
## Fine-tuning
- Method: LoRA
- Rank: 16
- Alpha: 32
- Dropout: 0.05
- Task: Causal Language Modeling
## Intended Use
Research and experimentation in Text-to-SQL generation.
## Limitations
Generated SQL should be validated before execution.
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