Update README.md

README.md

@@ -1,36 +1,39 @@
----
-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))
+---
+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.