| | --- |
| | language: en |
| | datasets: custom |
| | tags: |
| | - text-to-sql |
| | - t5 |
| | - natural-language-processing |
| | - transformers |
| | - huggingface |
| | license: apache-2.0 |
| | --- |
| | |
| | # 🔍 Text-to-SQL with T5 (`t5-base`) |
| |
|
| | This model is a fine-tuned version of [`t5-base`](https://huggingface.co/t5-base) on a custom **Text-to-SQL** dataset. It translates natural language questions into corresponding SQL queries. |
| |
|
| | ## 📌 Model Details |
| |
|
| | - **Base model:** [t5-base](https://huggingface.co/t5-base) |
| | - **Task:** Natural Language to SQL (text-to-SQL) |
| | - **Dataset:** Small custom dataset (~10–15 examples) of questions and SQL queries |
| | - **Language:** English |
| | - **Fine-tuned by:** [Priyanshu05](https://huggingface.co/Priyanshu05) |
| |
|
| | ## 🧠 Example |
| |
|
| | ```python |
| | from transformers import T5Tokenizer, T5ForConditionalGeneration |
| | |
| | model = T5ForConditionalGeneration.from_pretrained("Priyanshu05/text-to-sql-t5") |
| | tokenizer = T5Tokenizer.from_pretrained("Priyanshu05/text-to-sql-t5") |
| | |
| | question = "translate natural language to SQL: show all customers" |
| | inputs = tokenizer(question, return_tensors="pt") |
| | output = model.generate(**inputs) |
| | print(tokenizer.decode(output[0], skip_special_tokens=True)) |
| | ``` |
| | ## License |
| | This project is licensed under the Apache-2.0 License. |
