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---
license: mit
language:
- en
metrics:
- accuracy
pipeline_tag: text-generation
widget:
- text: "<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>"
example_title: "example1"
- text: "<schema>CREATE TABLE system(JobID: String,GID: String, UID: String,Submit: Time , Start:Time(yyyy/mm/dd), End: Time,ElapsedRaw: Time, CPUTimeRAW: Time,NCPUS: Number,NNodes: Number, NodeList: List, State:String, Timelimit: Time);</schema><question>Write sql query to get UID for JobID 20 that Start on Jan 20 , 2010 and end on March 10 , 2012 </question><sql>"
example_title: "example2"
tags:
- code
- sql
- text2sql
- instruction_tuned
- jax
- pytorch
- 1b
- expert
datasets:
- PipableAI/spider-bird
---
# Pipable’s pipSQL
Pipable’s pipSQL is a model distilled from llama 1b to generate sql queries given prompt and schema.
We used a unique pipeline which involved the model working on two objectives alternatively ----
1. Maximizing the log prob of all tokens in the sequence (including the prompt tokens)
2. Minimizng the difference between the true value and the predicted maximum value of the output tokens i.e generated tokens for the sql query slice of the entire sequence.
## License
The model's new weights along with all other assets involved with it are open sourced under mit license.
## How to Use
```python
text = """<schema>{schema}</schema>
<question>{question}</question>
<sql>"""
```
```python
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])
```
## The PipableAI team
Avi Kothari, Pratham Gupta, Ritvik Aryan Kalra, Rohan Bhatial, Soham Acharya , Gyan Ranjan |