Update main.py

main.py

@@ -1,93 +1,4 @@
-import matplotlib.pyplot as plt
-import numpy as np
-#
-# result=[(0, 1), (1, 3), (4, 4), (8, 3), (10, 6), (12, 3), (14, 2), (16, 1), (17, 0)]
-# y=[]
-# print(result)
-# x=[]
-# start = []
-# end = []
-# for i in range(len(result)-1):
-#     #x1=(result1[i][0],result1[i+1][0])
-#     for j in range(result[i][0],result[i+1][0]):
-#         x.append(j)
-#         y.append(result[i][1])
-# x.append(17)
-# y.append(0)
-# print(x)
-# print(y)
-# plt.bar(x,y,width=2)
-# plt.xlabel("X-coordinate")
-# plt.ylabel("Height")
-# plt.title("Skyline")
-# plt.show()
-# print(x)
-# print(y)
-# import gradio as gr
-#
-# from transformers import pipeline
 
-#
-# import gradio as gr
-# from transformers import pipeline
-# from googletrans import Translator
-# pipe = pipeline("translation_en_to_zh", model="t5-base", framework="tf")
-# translator = Translator(service_urls=['translate.google.com'])
-#
-#
-#
-#
-#
-# def translate(text):
-#     result = translator.translate(text, dest='zh-CN')
-#     return result.text
-#
-# with gr.Blocks() as demo:
-#     with gr.Row():
-#         with gr.Column():
-#             english = gr.Textbox(label="English text")
-#             translate_btn = gr.Button(value="Translate")
-#         with gr.Column():
-#             chinese = gr.Textbox(label="Chinese Text")
-#
-#     # translate_btn.click(translate, inputs=english, outputs=chinese, api_name="translate-to-chinese", share=True)
-#     with gr.Interface(fn=translate, inputs=gr.inputs.Textbox(label="English text"),
-#                       outputs=gr.outputs.Textbox(label="Chinese Text"),port=8888) as demo:
-#         demo.launch(share=True)
-#     examples = gr.Examples(examples=["I went to the supermarket yesterday.", "Helen is a good swimmer."],
-#                            inputs=[english])
-#
-#
-#
-# demo.launch()
-
-# import gradio as gr
-# from transformers import pipeline
-# import transformers
-# import os
-#
-# os.environ["HUGGINGFACE_API_TOKEN"] = "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"
-#
-# pipe = pipeline("translation", model="t5-base-zh-to-en", api_name="t5-base")
-#
-# def translate(text):
-#     return pipe(text)[0]["translation_text"]
-#
-# with gr.Interface(fn=translate, inputs="text", outputs="text", layout="vertical",
-#                   title="英文翻译成中文", description="使用Hugging Face的transformers库进行翻译") as iface:
-#     iface.launch()
-# import gradio as gr
-# from transformers import pipeline
-#
-# pipe = pipeline("translation_en_to_zh", model="t5-base", framework="tf")
-#
-#
-# def translate(text):
-#     return pipe(text)[0]["translation_text"]
-#
-#
-# with gr.Interface(fn=translate, inputs=gr.inputs.Textbox(label="English text"), outputs=gr.outputs.Textbox(label="Chinese Text")) as demo:
-#     demo.launch()
 
 import gradio as gr