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from transformers import AutoTokenizer
import transformers
import os
import sys
import fire
import torch
import gradio as gr
MAGICODER_PROMPT = """You are an exceptionally intelligent coding assistant that consistently delivers accurate and reliable responses to user instructions.
@@ Instruction
{instruction}
@@ Response
"""
css = """
#q-output {
max-height: 60vh;
overflow: auto;
}
"""
title = "<h1 style='text-align: center; margin-bottom: 1rem'>🎩 Magicoder</h1>"
description = """This is a playground for Magicoder-S-DS-6.7B! Follow us on Github: https://github.com/ise-uiuc/magicoder and Huggingface: https://huggingface.co/ise-uiuc.
💡 Tips: You can include more details in your instruction for Magicoder to write better code for you! Details can be, but not limited to, as follows:
1. Specify your programming language (e.g., "... in Python" and "... in Java")
2. Specify the external libraries/packages that are necessary in your task (e.g., "... using the turtle library" and "Write a gradio application to ...")
3. Demonstrate your requirements as clear and comprehensive as possible (e.g., "use CNN as the model structure" and "draw a chart of the training loss")"""
def main(
base_model="ise-uiuc/Magicoder-S-DS-6.7B"
):
pipeline = transformers.pipeline(
"text-generation", model=base_model, torch_dtype=torch.bfloat16, device_map="auto"
)
def evaluate_magicoder(
instruction,
temperature=1,
max_length=2048,
):
prompt = MAGICODER_PROMPT.format(instruction=instruction)
if temperature > 0:
sequences = pipeline(
prompt,
do_sample=True,
temperature=temperature,
max_length=max_length,
)
else:
sequences = pipeline(
prompt,
max_length=max_length,
)
for seq in sequences:
generated_text = seq["generated_text"].replace(prompt, "")
return generated_text
with gr.Blocks(css=css) as demo:
gr.Markdown(title)
gr.Markdown(description)
with gr.Row(equal_height=True):
with gr.Column(variant="default"):
interface_input = gr.Textbox(
lines=3,
label="Instruction",
placeholder="Anything you want to ask Magicoder ?",
value="Write a snake game in Python using the turtle library (the game is created by Magicoder).",
)
temperature = gr.Slider(minimum=0, maximum=1, value=0, label="Temperature")
max_new_tokens = gr.Slider(
minimum=1, maximum=2048, step=1, value=2048, label="Max tokens"
)
submit = gr.Button(value="Generate")
gr.Examples(
examples=[
["Write a snake game in Python using the turtle library (the game is created by Magicoder)."],
["Build a console-based Othello game in Java with row and column numbers shown on the board. The game should end when there are no more valid moves for either player."],
["Write a gradio (3.48.0) application for the following use case: Take an input image and return a 45 degree clockwise rotated image. You should also add text description under the output showing the rotation degree."],
["Build a simple neural network in Python using Pytorch to classify handwritten digits from the MNIST dataset. You should use CNN as the model structure, train the model for 5 epochs, draw a chart of the training loss, and show the final result."],
],
inputs = [interface_input]
)
with gr.Column(variant="default"):
with gr.Tab("Output", elem_id="q-output"):
output = gr.Markdown(
label="Output"
)
submit.click(
evaluate_magicoder,
inputs=[interface_input, temperature, max_new_tokens],
outputs=[output],
)
demo.queue().launch()
if __name__ == "__main__":
fire.Fire(main)
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