| 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)) |