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README.md

@@ -1,22 +1,61 @@
+
 ---
-base_model: unsloth/mistral-7b-instruct-v0.3-bnb-4bit
+language: en
+license: apache-2.0
 tags:
-- text-generation-inference
-- transformers
-- unsloth
 - mistral
-- trl
-license: apache-2.0
-language:
-- en
+- sql
+- lora
+- instruction-tuning
+datasets:
+- custom_sql_dataset
 ---
 
-# Uploaded  model
+# SQL Query Generation Model
+
+This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 specialized for SQL query generation.
+
+## Model Details
+
+- **Base Model**: mistralai/Mistral-7B-Instruct-v0.3
+- **Training Method**: LoRA (Rank=16, Alpha=32)
+- **Task**: SQL query generation from natural language instructions
+- **Training Framework**: Unsloth
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+# Load the model
+tokenizer = AutoTokenizer.from_pretrained("exaler/aaa-2-sql-2")
+model = AutoModelForCausalLM.from_pretrained("exaler/aaa-2-sql-2")
+
+# Format your prompt
+instruction = """You are an expert SQL query generator. Database schema:
+Table: [dbo].[Users]
+Columns: [ID], [Name], [Email], [CreatedDate]
+Table: [dbo].[Orders]
+Columns: [OrderID], [UserID], [Amount], [Status], [OrderDate]
+"""
+
+input_text = "Find all users who placed orders with amount greater than 1000"
+
+prompt = f"<s>[INST] {instruction}\n\n{input_text} [/INST]"
+
+# Generate SQL
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+outputs = model.generate(inputs=inputs.input_ids, max_new_tokens=512, temperature=0.0)
+response = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
+print(response)
+```
+
+## Training Dataset
 
-- **Developed by:** exaler
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/mistral-7b-instruct-v0.3-bnb-4bit
+The model was trained on a custom dataset of SQL queries with their corresponding natural language descriptions.
 
-This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+## Limitations
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+- The model is optimized for the specific SQL database schema it was trained on
+- Performance may vary for database schemas significantly different from the training data