Create README.md

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen3.5-0.8B
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+  - text-to-sql
+  - sql
+  - qwen
+  - demo
+  - vertex-ai
+  - synthetic-data
+---
+
+# qwen35-08b-text2sql
+
+`Tuana/qwen35-08b-text2sql` is a **demo Text-to-SQL model** fine-tuned from [`Qwen/Qwen3.5-0.8B`](https://huggingface.co/Qwen/Qwen3.5-0.8B).
+
+It was fine-tuned on a small, specific synthetic SQL dataset for demonstration purposes. It is not intended to be a general Text-to-SQL model for arbitrary schemas or production databases.
+
+## Model Details
+
+- **Base model:** `Qwen/Qwen3.5-0.8B`
+- **Task demo:** Text-to-SQL style SQL generation
+- **Fine-tuning method:** LoRA SFT, merged into a full checkpoint
+- **Training platform:** Google Cloud Vertex AI
+- **Training container:** Hugging Face PyTorch Training Deep Learning Container
+- **Dataset:** `Tuana/synthetic-sql-dataset`
+- **Model format:** Merged `transformers` checkpoint
+
+## What This Model Demonstrates
+
+This model demonstrates a small fine-tuning workflow:
+
+1. Generate a synthetic SQL instruction dataset
+2. Fine-tune a small Qwen base model on Vertex AI
+3. Merge the LoRA adapter into the base checkpoint
+4. Serve or compare the result in a small demo app
+
+The demo dataset uses a small synthetic database domain with tables such as:
+
+- `department`
+- `management`
+- `head`
+
+The model should be viewed as a demo artifact for this specific setup, not as a robust SQL assistant.
+
+## Example Prompt Format
+
+```text
+Given this database schema:
+CREATE TABLE department (
+  department_id VARCHAR,
+  name VARCHAR,
+  creation VARCHAR
+);
+CREATE TABLE management (
+  department_id VARCHAR,
+  head_id VARCHAR,
+  temporary_acting VARCHAR
+);
+CREATE TABLE head (
+  head_id VARCHAR,
+  name VARCHAR,
+  born_state VARCHAR
+);
+
+Write a SQL query for:
+List all department names.
+
+SQL:
+```