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| import gradio as gr | |
| from transformers import pipeline | |
| def text_pipelines(text_txt, text_pipes): | |
| if text_pipes == "Translate En to Fr": | |
| en_fr_translator = pipeline("translation_en_to_fr") | |
| output = en_fr_translator(f"{text_txt}")[0]["translation_text"] | |
| elif text_pipes == "Text Generation": | |
| text_generation = pipeline("text-generation") | |
| output = text_generation(f"{text_txt}")[0]["generated_text"] | |
| elif text_pipes == "Sentiment Analysis": | |
| sentiment_analysis = pipeline("sentiment-analysis") | |
| output = sentiment_analysis(f"{text_txt}") | |
| return output | |
| def cat_images(cat_slider): | |
| if cat_slider < 10: | |
| images = ["./images/dog1.jpg", "./images/dog2.jpg"] | |
| if cat_slider >= 10: | |
| images = ["./images/cat1.jpg", "./images/cat2.jpg", "./images/cat3.jpg"] | |
| return images | |
| with gr.Blocks() as Blocks: | |
| with gr.Row(): | |
| gr.Markdown("<h1>🤗 Hugging Face Pipelines 🤗</h1> <h2>🥳🥳 Welcome to the block party! 🥳🥳</h2>") | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Markdown("<br><br><br><br>") | |
| with gr.Tabs(): | |
| with gr.TabItem("Audio Classification"): | |
| gr.Markdown("<h3>🔊Audio Classification</h3><p>Classifies your audio!</p><p>You could: Label emotions, such as happy or sad.😊😢</p>") | |
| with gr.TabItem("Automatic Speech Recognition"): | |
| gr.Markdown("<h3>💬Automatic Speech Recognition</h3><p>Recognizes speech automatically!</p><p>You could: Create transcripts. 📃</p>") | |
| with gr.TabItem("Image Segmentation"): | |
| gr.Markdown("<h3>🖼️Image Segmentation</h3><p>Segments images!</p><p>You could: Highlight the area that has a cat</p") | |
| gr.Markdown("<br><br><p>There are all kinds of pipelines: image, text, audio!</p><p>⬇️ Try some of them out below ⬇️</p>") | |
| with gr.Column(): | |
| gr.Markdown("<br><br>") | |
| with gr.Column(): | |
| with gr.Tabs(): | |
| with gr.TabItem("What's a Pipeline?!"): | |
| gr.Markdown("Easy mode! Use the pipeline() to streamline everything in like 4 lines of code. It's even smart enough to pick a model for you if you want. 🤗") | |
| with gr.TabItem("What's Gradio?"): | |
| gr.Markdown("The way to make layouts super quickly! You can add dropdown boxes, radio buttons, checkboxes and more which will be able to change the inputs to your functions.") | |
| with gr.Tabs(): | |
| with gr.TabItem("Block Party!"): | |
| gr.Markdown("<p>This was created during Hugging Face's Block Party to celebrate the release of Gradio's new block function.</p><p>The app was created using a block with 4 rows, and the info box you are reading was made using Gradio Tabs!</p><p>Thank you ever so much for your likes! ❤️</p>") | |
| with gr.TabItem("Cat Tax"): | |
| cat_slider = gr.Slider(0, 100, label="Percentage you like cats:") | |
| cats_but = gr.Button("Show cute cats!") | |
| gallery = gr.Gallery() | |
| with gr.Row(): | |
| gr.Markdown("<h1>🚀 Test Out Some Text Pipelines! 🚀") | |
| with gr.Row(): | |
| text_txt = gr.Textbox("Enter something fun here!", label="1. Type some text:") | |
| text_pipes = gr.Dropdown(["Translate En to Fr", "Text Generation", "Sentiment Analysis"], label="2. Pick your Pipeline:") | |
| go_but = gr.Button("3. It's go time!") | |
| text = gr.Textbox("Hit the go button to see results here", label="4. See the output!") | |
| cats_but.click(cat_images, inputs=cat_slider, outputs=gallery) | |
| go_but.click(text_pipelines, inputs=[text_txt, text_pipes], outputs=text) | |
| Blocks.launch() |