🚀 Pipable的pipSQL

Pipable的pipSQL是一个从llama 1b蒸馏而来的模型，可根据给定的提示和模式生成SQL查询。该模型在许多基准测试的SQL任务中表现优于ChatGPT和Claude。

🚀 快速开始

请参考https://huggingface.co/PipableAI/pipSQL-1.3b获取我们的先进模型，它在许多基准测试的SQL任务中比ChatGPT和Claude表现更好。

✨ 主要特性

Pipable的pipSQL使用了独特的管道，让模型交替完成两个目标：

1. 最大化序列中所有标记（包括提示标记）的对数概率。
2. 最小化输出标记（即整个序列中SQL查询部分的生成标记）的真实值与预测最大值之间的差异。

📦 安装指南

暂未提供相关安装步骤。

💻 使用示例

基础用法

text = """<schema>{schema}</schema>
<question>{question}</question>
<sql>"""

高级用法

PyTorch

from transformers import AutoModelForCasualLM, AutoTokenizer
device = "cuda"
model = AutoModelForCausalLM.from_pretrained("PipableAI/pipSQL1b")
tokenizer = AutoTokenizer.from_pretrained("PipableAI/pipSQL1b")

inputs = tokenizer(text, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True).split('<sql>')[1].split('</sql>')[0])

Flax

from transformers import FlaxAutoModelForCasualLM, AutoTokenizer
model = FlaxAutoModelForCausalLM.from_pretrained("PipableAI/pipSQL1b" , from_pt=True)
tokenizer = AutoTokenizer.from_pretrained("PipableAI/pipSQL1b")

📚 详细文档

模型信息

示例输入

• 示例1：

<schema>CREATE TABLE radio(age VARCHAR, radio_id VARCHAR,  frequency VARCHAR, wavelength VARCHAR); CREATE TABLE  radio_faults(radio_id VARCHAR, fault_description VARCHAR)</schema><question>Get the radio id and defect descriptions of radios that have wavelength greater than 30 ?</question><sql>

• 示例2：

<schema>CREATE TABLE system(JobID: String,GID: String, UID: String, Start:Time(yyyy/mm/dd), End: Time,ElapsedRaw: Time, CPUTimeRAW: Time,NCPUS: Number,NNodes: Number, NodeList: List,  State:String, Timelimit: Time);</schema><question>Get UID and job id for Jobs that started on Jan 20 , 2023</question><sql>

• 示例3：

<schema>CREATE TABLE department (Department_ID number, Name text, Creation text, Ranking number, Budget_in_Billions number, Num_Employees number) which has Department_ID as primary key abd CREATE TABLE head (head_ID number, name text, born_state text, age number) which has head_ID as primary key and CREATE TABLE management (department_ID number, head_ID number, temporary_acting text) which has department_ID as primary key</schema><question>

📄 许可证

该模型的新权重以及所有相关资产均在MIT许可证下开源。

👥 PipableAI团队

Avi Kothari、Pratham Gupta、Ritvik Aryan Kalra、Rohan Bhatial、Soham Acharya