SQL-chat / app.py
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import gradio as gr
import os
os.environ["KERAS_BACKEND"] = "tensorflow"
import keras
import keras_nlp
css = ".body {background-image: url('https://www.universetoday.com/wp-content/uploads/2023/11/Sagittarius_C_NIRCam_Image_pillars-2000x1080.jpg'); background-color: transparent;}"
gemma_lm = keras_nlp.models.CausalLM.from_preset("hf://sultan-hassan/CosmoGemma_2b_en")
def launch(input):
template = "Instruction:\n{instruction}\n\nResponse:\n{response}"
prompt = template.format(
instruction=input,
response="",
)
out = gemma_lm.generate(prompt, max_length=256)
ind = out.index('Response') + len('Response')+2
return out[ind:]
iface = gr.Interface(launch,
inputs="text",
outputs="text",
css=css,
title="Hello, I am an expert in cosmology, try me!",
description="Gemma_2b_en fine-tuned on QA pairs (~3.5k) generated from Cosmology and Nongalactic Astrophysics articles (arXiv astro-ph.CO) from 2018-2022 and tested on QA pairs (~1k) generated from 2023 articles, scoring over 75% accuracy.")
iface.launch(share=True)