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README.md

@@ -1,12 +1,11 @@
+
 ---
-title: Unified Demo Text Generation Main
-emoji: 🐨
+title: unified_demo_text_generation_main 
+emoji: 🔥
 colorFrom: indigo
-colorTo: pink
+colorTo: indigo
 sdk: gradio
-sdk_version: 3.17.0
-app_file: app.py
+sdk_version: 3.17.1
+app_file: run.py
 pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

requirements.txt

@@ -0,0 +1,3 @@
+torch
+transformers
+https://gradio-main-build.s3.amazonaws.com/f3b3736596d9c0eb08613da1e19e5dc9b61286e3/gradio-3.17.1-py3-none-any.whl

run.ipynb

@@ -0,0 +1 @@
+{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: unified_demo_text_generation"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio torch transformers"]}, {"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(text_prompt):\n", "  response = generator(text_prompt, max_length = 30, num_return_sequences=5)\n", "  return response[0]['generated_text']\n", "\n", "textbox = gr.Textbox()\n", "\n", "demo = gr.Interface(generate_text, textbox, textbox)\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -0,0 +1,15 @@
+import gradio as gr
+from transformers import pipeline
+
+generator = pipeline('text-generation', model = 'gpt2')
+
+def generate_text(text_prompt):
+  response = generator(text_prompt, max_length = 30, num_return_sequences=5)
+  return response[0]['generated_text']
+
+textbox = gr.Textbox()
+
+demo = gr.Interface(generate_text, textbox, textbox)
+
+if __name__ == "__main__":
+    demo.launch()