Upload folder using huggingface_hub

README.md

@@ -5,7 +5,7 @@ emoji: 🔥
 colorFrom: indigo
 colorTo: indigo
 sdk: gradio
-sdk_version: 5.49.1
+sdk_version: 6.0.0
 app_file: run.py
 pinned: false
 hf_oauth: true

requirements.txt

@@ -1,2 +1,2 @@
-gradio-client @ git+https://github.com/gradio-app/gradio@e05eb8df38a4ca20993e94ca4e209cf8110bb677#subdirectory=client/python
-https://gradio-pypi-previews.s3.amazonaws.com/e05eb8df38a4ca20993e94ca4e209cf8110bb677/gradio-5.49.1-py3-none-any.whl
+gradio-client @ git+https://github.com/gradio-app/gradio@d007e6cf617baba5c62e49ec2b7ce278aa863a79#subdirectory=client/python
+https://gradio-pypi-previews.s3.amazonaws.com/d007e6cf617baba5c62e49ec2b7ce278aa863a79/gradio-6.0.0-py3-none-any.whl

run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: interface_random_slider"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "def func(slider_1, slider_2, *args):\n", "    return slider_1 + slider_2 * 5\n", "\n", "demo = gr.Interface(\n", "    func,\n", "    [\n", "        gr.Slider(minimum=1.5, maximum=250000.89, randomize=True, label=\"Random Big Range\"),\n", "        gr.Slider(minimum=-1, maximum=1, randomize=True, step=0.05, label=\"Random only multiple of 0.05 allowed\"),\n", "        gr.Slider(minimum=0, maximum=1, randomize=True, step=0.25, label=\"Random only multiples of 0.25 allowed\"),\n", "        gr.Slider(minimum=-100, maximum=100, randomize=True, step=3, label=\"Random between -100 and 100 step 3\"),\n", "        gr.Slider(minimum=-100, maximum=100, randomize=True, label=\"Random between -100 and 100\"),\n", "        gr.Slider(value=0.25, minimum=5, maximum=30, step=-1),\n", "    ],\n", "    \"number\",\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: interface_random_slider"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "\n", "def func(slider_1, slider_2, *args):\n", "    return slider_1 + slider_2 * 5\n", "\n", "demo = gr.Interface(\n", "    func,\n", "    [\n", "        gr.Slider(minimum=1.5, maximum=250000.89, randomize=True, label=\"Random Big Range\"),\n", "        gr.Slider(minimum=-1, maximum=1, randomize=True, step=0.05, label=\"Random only multiple of 0.05 allowed\"),\n", "        gr.Slider(minimum=0, maximum=1, randomize=True, step=0.25, label=\"Random only multiples of 0.25 allowed\"),\n", "        gr.Slider(minimum=-100, maximum=100, randomize=True, step=3, label=\"Random between -100 and 100 step 3\"),\n", "        gr.Slider(minimum=-100, maximum=100, randomize=True, label=\"Random between -100 and 100\"),\n", "        gr.Slider(value=0.25, minimum=5, maximum=30, step=-1),\n", "    ],\n", "    \"number\",\n", "    api_name=\"predict\"\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -14,6 +14,7 @@ demo = gr.Interface(
         gr.Slider(value=0.25, minimum=5, maximum=30, step=-1),
     ],
     "number",
+    api_name="predict"
 )
 
 if __name__ == "__main__":