Spaces:
Running
Running
File size: 1,057 Bytes
4614c9a 4920445 4614c9a 8da08ab 4920445 8da08ab 4920445 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 |
<!DOCTYPE html>
<html>
<head>
<script type="module" crossorigin src="https://cdn.jsdelivr.net/npm/@gradio/[email protected]/dist/lite.js"></script>
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@gradio/[email protected]/dist/lite.css" />
</head>
<body>
<h2>Gradio-lite (Gradio running entirely in your browser!)</h2>
<h4>Try it out! Once the Gradio app loads (can take 10-15 seconds), disconnect your Wifi and the machine learning model will still work!</h4>
<gradio-lite>
<gradio-requirements>
transformers_js_py
</gradio-requirements>
<gradio-file name="app.py" entrypoint>
from transformers_js import import_transformers_js
import gradio as gr
transformers = await import_transformers_js()
pipeline = transformers.pipeline
pipe = await pipeline('sentiment-analysis')
async def classify(text):
return await pipe(text)
demo = gr.Interface(classify, "textbox", "json", examples=["It's a happy day in the neighborhood", "I'm an evil penguin", "It wasn't a bad film."])
demo.launch()
</gradio-file>
</gradio-lite>
</body>
</html> |