Create README.md

README.md

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+---
+base_model: deepseek-ai/deepseek-coder-6.7b-instruct
+tags:
+- SOLAR
+- instruct
+- finetune
+model-index:
+- name: NaturalQuery-Solar-6.7B-v0.1
+  results: []
+license: apache-2.0
+language:
+- en
+datasets:
+- wikisql
+---
+
+# **NaturalQuery-Solar-6.7B-v0.1**
+
+**NaturalQuery** is a LLM that can translate natural language queries to SQL based on your schema.
+
+NaturalQuery-v0.1 is finetuned on 8k text to PostgreSQL Natural Language <> SQL pairs.
+
+**Future Improvements**:
+
+- Much larger training set
+- More complex schemas, questions, and queries
+- Reward modeling via DPO
+- Benchmarking
+
+# **Usage**
+
+Make sure you have the correct version of the transformers library installed:
+
+```sh
+pip install transformers==4.35.2
+```
+
+### **Loading the Model**
+
+Use the following Python code to load the model:
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+tokenizer = AutoTokenizer.from_pretrained("cfahlgren1/NaturalSQL-6.7B-v0")
+model = AutoModelForCausalLM.from_pretrained(
+    "cfahlgren1/NaturalSQL-6.7B-v0",
+    device_map="auto",
+    torch_dtype=torch.float16,
+)
+```
+
+### **Generating Text**
+
+To generate text, use the following Python code:
+
+```python
+text = "Hi, my name is "
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=64)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+
+# **SQL Generation Template**
+
+```
+### Task 
+
+Generate a SQL query to answer the following question: `{natural language question}` 
+
+### Database Schema 
+
+The query will run on a database with the following schema: 
+
+'''
+<SQL Table DDL Statements>
+'''
+
+### Answer 
+Here is the SQL query that answers the question: `{natural language question}` 
+'''sql
+```
+
+# **Example SQL Output**
+
+### **Example Schemas**
+
+```sql
+ CREATE TABLE
+      table_1_11545282_6 (
+        "No." numeric,
+        Nationality text,
+        "Years for Jazz" text
+      );
+    
+    CREATE TABLE
+      table_2_17383560_1 (
+        Pick numeric,
+        Round numeric,
+        Player text,
+        "School/Club Team" text,
+        Position text
+      );
+    
+    CREATE TABLE
+      table_1_10581768_2 (
+        Institution text,
+        Enrollment numeric,
+        Nickname text,
+        Founded numeric
+      );
+```
+
+**Question**: **What is the round of pick 63?**
+```sql
+SELECT "Round" FROM table_2_17383560_1 WHERE Pick=63;
+```
+**Question**: **What is the most popular position among players?**
+```sql
+SELECT COUNT("Position") FROM "table_2_17383560_1" GROUP BY "Position" ORDER BY COUNT("Position") DESC LIMIT 1;
+```
+
+**Question**: **What is the most recent year an institution was founded?**
+```sql
+SELECT MAX("Founded") FROM table_1_10581768_2;
+```