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Update app.py
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import gradio as gr
from transformers import (
AutoModelForSeq2SeqLM,
AutoTokenizer,
AutoConfig,
pipeline,
)
model_name = "sagard21/python-code-explainer"
tokenizer = AutoTokenizer.from_pretrained(model_name, padding=True)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
config = AutoConfig.from_pretrained(model_name)
model.eval()
pipe = pipeline("summarization", model=model_name, config=config, tokenizer=tokenizer)
def generate_text(text_prompt):
response = pipe(text_prompt)
return response[0]['summary_text']
textbox1 = gr.Textbox(value = """
class Solution(object):
def isValid(self, s):
stack = []
mapping = {")": "(", "}": "{", "]": "["}
for char in s:
if char in mapping:
top_element = stack.pop() if stack else '#'
if mapping[char] != top_element:
return False
else:
stack.append(char)
return not stack""")
textbox2 = gr.Textbox()
if __name__ == "__main__":
gr.Textbox("The Inference Takes about 1 min 30 seconds")
with gr.Blocks() as demo:
gr.Interface(fn = generate_text, inputs = textbox1, outputs = textbox2)
with gr.Row():
gr.Image(value = "output.jpg", label = "Sample Explaination in Natural Language")
gr.Image(value = "code.jpg", label = "Sample Code for Checking if a Binary Tree is Mirrored")
demo.launch()