Duplicate from sharpbai/text_generation

Co-authored-by: Tim Bai <sharpbai@users.noreply.huggingface.co>

.gitattributes

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DESCRIPTION.md

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+This text generation demo takes in input text and returns generated text. It uses the Transformers library to set up the model and has two examples.

README.md

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+---
+title: text_generation
+emoji: 🔥
+colorFrom: indigo
+colorTo: indigo
+sdk: gradio
+sdk_version: 3.33.1
+app_file: run.py
+pinned: false
+duplicated_from: sharpbai/text_generation
+---

app.py

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+import gradio as gr
+from transformers import pipeline
+
+generator = pipeline('text-generation', model='gpt2')
+
+def generate(text):
+    result = generator(text, max_length=256, num_return_sequences=1)
+    return result[0]["generated_text"]
+
+examples = [
+    ["The Moon's orbit around Earth has"],
+    ["The smooth Borealis basin in the Northern Hemisphere covers 40%"],
+]
+
+demo = gr.Interface(
+    fn=generate,
+    inputs=gr.inputs.Textbox(lines=5, label="Input Text"),
+    outputs=gr.outputs.Textbox(label="Generated Text"),
+    examples=examples
+)
+
+demo.launch()

requirements.txt

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+git+https://github.com/huggingface/transformers
+gradio
+torch

run.ipynb

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+{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: text_generation\n", "### This text generation demo takes in input text and returns generated text. It uses the Transformers library to set up the model and has two examples.\n", "        "]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio git+https://github.com/huggingface/transformers gradio torch"]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from transformers import pipeline\n", "\n", "generator = pipeline('text-generation', model='gpt2')\n", "\n", "def generate(text):\n", "    result = generator(text, max_length=30, num_return_sequences=1)\n", "    return result[0][\"generated_text\"]\n", "\n", "examples = [\n", "    [\"The Moon's orbit around Earth has\"],\n", "    [\"The smooth Borealis basin in the Northern Hemisphere covers 40%\"],\n", "]\n", "\n", "demo = gr.Interface(\n", "    fn=generate,\n", "    inputs=gr.inputs.Textbox(lines=5, label=\"Input Text\"),\n", "    outputs=gr.outputs.Textbox(label=\"Generated Text\"),\n", "    examples=examples\n", ")\n", "\n", "demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

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+import gradio as gr
+from transformers import pipeline
+
+generator = pipeline('text-generation', model='gpt2')
+
+def generate(text):
+    result = generator(text, max_length=30, num_return_sequences=1)
+    return result[0]["generated_text"]
+
+examples = [
+    ["The Moon's orbit around Earth has"],
+    ["The smooth Borealis basin in the Northern Hemisphere covers 40%"],
+]
+
+demo = gr.Interface(
+    fn=generate,
+    inputs=gr.inputs.Textbox(lines=5, label="Input Text"),
+    outputs=gr.outputs.Textbox(label="Generated Text"),
+    examples=examples
+)
+
+demo.launch()