Create README.md

README.md

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+---
+base_model: onekq-ai/OneSQL-v0.1-Qwen-7B
+tags:
+- text-generation-inference
+- transformers
+- qwen2
+- mlx
+license: apache-2.0
+language:
+- en
+---
+
+# Introduction
+
+This model is the MLX version of [OneSQL-v0.1-Qwen-7B](https://huggingface.co/onekq-ai/OneSQL-v0.1-Qwen-7B). It is made for Apple Silicon.
+
+# Performances
+
+The self-evaluation EX score of the original model is **56.19** (compared to **63.33** by the 32B model on the [BIRD leaderboard](https://bird-bench.github.io/).
+The self-evaluation EX score of this AWQ model is **51.69**.
+
+# Quick start
+
+To use this model, craft your prompt to start with your database schema in the form of **CREATE TABLE**, followed by your natural language query preceded by **--**.
+Make sure your prompt ends with **SELECT** in order for the model to finish the query for you. There is no need to set other parameters like temperature or max token limit.
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("model="onekq-ai/OneSQL-v0.1-Qwen-7B-MLX-4bit")
+
+prompt="""CREATE TABLE students (
+    id INTEGER PRIMARY KEY,
+    name TEXT,
+    age INTEGER,
+    grade TEXT
+);
+
+-- Find the three youngest students
+SELECT """
+
+response = generate(model, tokenizer, f"<|im_start|>system\nYou are a SQL expert. Return code only.<|im_end|>\n<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n")
+print(response)
+```
+
+The model response is the finished SQL query without **SELECT**
+```sql
+* FROM students ORDER BY age ASC LIMIT 3
+```
+
+# User Experience
+
+Speed benchmark of this model is obtained on a MacBook Air with M1 processor and 8GB of RAM, the lower bound of Apple Silicon.
+On average, it took 16 seconds to generate a SQL query at 9 characters per second.