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README.md

@@ -5,7 +5,7 @@ emoji: 🔥
 colorFrom: indigo
 colorTo: indigo
 sdk: gradio
-sdk_version: 4.3.0
+sdk_version: 4.4.0
 app_file: run.py
 pinned: false
 hf_oauth: true

run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: automatic-speech-recognition\n", "### Automatic speech recognition English. Record from your microphone and the app will transcribe the audio.\n", "        "]}, {"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", "import os\n", "\n", "# save your HF API token from https:/hf.co/settings/tokens as an env variable to avoid rate limiting\n", "auth_token = os.getenv(\"auth_token\")\n", "\n", "# automatically load the interface from a HF model \n", "# you can remove the api_key parameter if you don't care about rate limiting. \n", "demo = gr.load(\n", "    \"huggingface/facebook/wav2vec2-base-960h\",\n", "    title=\"Speech-to-text\",\n", "    inputs=\"mic\",\n", "    description=\"Let me try to guess what you're saying!\",\n", "    hf_token=auth_token\n", ")\n", "\n", "demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: automatic-speech-recognition\n", "### Automatic speech recognition English. Record from your microphone and the app will transcribe the audio.\n", "        "]}, {"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", "import os\n", "\n", "# save your HF API token from https:/hf.co/settings/tokens as an env variable to avoid rate limiting\n", "hf_token = os.getenv(\"hf_token\")\n", "\n", "# automatically load the interface from a HF model \n", "# you can remove the hf_token parameter if you don't care about rate limiting. \n", "demo = gr.load(\n", "    \"huggingface/facebook/wav2vec2-base-960h\",\n", "    title=\"Speech-to-text\",\n", "    inputs=\"mic\",\n", "    description=\"Let me try to guess what you're saying!\",\n", "    hf_token=hf_token\n", ")\n", "\n", "demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -2,16 +2,16 @@ import gradio as gr
 import os
 
 # save your HF API token from https:/hf.co/settings/tokens as an env variable to avoid rate limiting
-auth_token = os.getenv("auth_token")
+hf_token = os.getenv("hf_token")
 
 # automatically load the interface from a HF model 
-# you can remove the api_key parameter if you don't care about rate limiting. 
+# you can remove the hf_token parameter if you don't care about rate limiting. 
 demo = gr.load(
     "huggingface/facebook/wav2vec2-base-960h",
     title="Speech-to-text",
     inputs="mic",
     description="Let me try to guess what you're saying!",
-    hf_token=auth_token
+    hf_token=hf_token
 )
 
 demo.launch()