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requirements.txt

@@ -1,4 +1,4 @@
-gradio-client @ git+https://github.com/gradio-app/gradio@de997e67c9a7feb9e2eccebf92969366dbd67eba#subdirectory=client/python
-https://gradio-builds.s3.amazonaws.com/de997e67c9a7feb9e2eccebf92969366dbd67eba/gradio-4.39.0-py3-none-any.whl
+gradio-client @ git+https://github.com/gradio-app/gradio@9b42ba8f1006c05d60a62450d3036ce0d6784f86#subdirectory=client/python
+https://gradio-builds.s3.amazonaws.com/9b42ba8f1006c05d60a62450d3036ce0d6784f86/gradio-4.39.0-py3-none-any.whl
 transformers
 torch

run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: english_translator"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio transformers torch"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "from transformers import pipeline\n", "\n", "pipe = pipeline(\"translation\", model=\"t5-base\")\n", "\n", "\n", "def translate(text):\n", "    return pipe(text)[0][\"translation_text\"]  # type: ignore\n", "\n", "\n", "with gr.Blocks() as demo:\n", "    with gr.Row():\n", "        with gr.Column():\n", "            english = gr.Textbox(label=\"English text\")\n", "            translate_btn = gr.Button(value=\"Translate\")\n", "        with gr.Column():\n", "            german = gr.Textbox(label=\"German Text\")\n", "\n", "    translate_btn.click(translate, inputs=english, outputs=german, api_name=\"translate-to-german\")\n", "    examples = gr.Examples(examples=[\"I went to the supermarket yesterday.\", \"Helen is a good swimmer.\"],\n", "                           inputs=[english])\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: english_translator"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio transformers torch"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "from transformers import pipeline\n", "\n", "pipe = pipeline(\"translation\", model=\"t5-base\")\n", "\n", "def translate(text):\n", "    return pipe(text)[0][\"translation_text\"]  # type: ignore\n", "\n", "with gr.Blocks() as demo:\n", "    with gr.Row():\n", "        with gr.Column():\n", "            english = gr.Textbox(label=\"English text\")\n", "            translate_btn = gr.Button(value=\"Translate\")\n", "        with gr.Column():\n", "            german = gr.Textbox(label=\"German Text\")\n", "\n", "    translate_btn.click(translate, inputs=english, outputs=german, api_name=\"translate-to-german\")\n", "    examples = gr.Examples(examples=[\"I went to the supermarket yesterday.\", \"Helen is a good swimmer.\"],\n", "                           inputs=[english])\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -4,11 +4,9 @@ from transformers import pipeline
 
 pipe = pipeline("translation", model="t5-base")
 
-
 def translate(text):
     return pipe(text)[0]["translation_text"]  # type: ignore
 
-
 with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column():
@@ -22,4 +20,4 @@ with gr.Blocks() as demo:
                            inputs=[english])
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()