Spaces:
Runtime error
Runtime error
File size: 6,664 Bytes
8eb2c7a 5290d3e 8eb2c7a 5290d3e 8eb2c7a 5290d3e 8eb2c7a 5290d3e 8eb2c7a 5290d3e 8eb2c7a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 |
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"gpuType": "T4"
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "markdown",
"source": [
"# Whisper v3 is here!\n",
"\n",
"Whisper v3 is a new model open sourced by OpenAI. The model can do multilingual transcriptions and is quite impressive. For example, you can change from English to Spanish or Chinese in the middle of a sentence and it will work well!\n",
"\n",
"The model can be run in a free Google Colab instance and is integrated into `transformers` already, so switching can be a very smooth process if you already use the previous versions."
],
"metadata": {
"id": "OXaUqiE-eyXM"
}
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "WFQeUT9EcIcK"
},
"outputs": [],
"source": [
"%%capture\n",
"!pip install git+https://github.com/huggingface/transformers gradio"
]
},
{
"cell_type": "markdown",
"source": [
"Let's use the high level `pipeline` from the `transformers` library to load the model."
],
"metadata": {
"id": "sZONes21fHTA"
}
},
{
"cell_type": "code",
"source": [
"import torch\n",
"from transformers import pipeline\n",
"\n",
"pipe = pipeline(\"automatic-speech-recognition\",\n",
" \"openai/whisper-large-v3\",\n",
" torch_dtype=torch.float16,\n",
" device=\"cuda:0\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "DvBdwMdPcr-Y",
"outputId": "47f32218-fd85-49ea-d880-d31577bcf9b8"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n",
"Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"pipe(\"https://cdn-media.huggingface.co/speech_samples/sample1.flac\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "GZFkIyhjc0Nc",
"outputId": "f1463431-3e08-4438-815f-b71e5e7a1503"
},
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"{'text': \" going along slushy country roads and speaking to damp audiences in draughty schoolrooms day after day for a fortnight he'll have to put in an appearance at some place of worship on sunday morning and he can come to us immediately afterwards\"}"
]
},
"metadata": {},
"execution_count": 2
}
]
},
{
"cell_type": "markdown",
"source": [
"Let's now build a quick Gradio demo where we can play with the model directly using our microphone! You can run this code in a Google Colab instance (or locally!) or just head to the <a href=\"https://huggingface.co./spaces/hf-audio/whisper-large-v3\" target=\"_blank\">Space</a> to play directly with it online."
],
"metadata": {
"id": "pt3YtM_PfTQY"
}
},
{
"cell_type": "code",
"source": [
"import gradio as gr\n",
"\n",
"def transcribe(inputs):\n",
" if inputs is None:\n",
" raise gr.Error(\"No audio file submitted! Please record an audio before submitting your request.\")\n",
"\n",
" text = pipe(inputs, generate_kwargs={\"task\": \"transcribe\"}, return_timestamps=True)[\"text\"]\n",
" return text\n",
"\n",
"demo = gr.Interface(\n",
" fn=transcribe,\n",
" inputs=[\n",
" gr.Audio(sources=[\"microphone\", \"upload\"], type=\"filepath\"),\n",
" ],\n",
" outputs=\"text\",\n",
" title=\"Whisper Large V3: Transcribe Audio\",\n",
" description=(\n",
" \"Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the\"\n",
" \" checkpoint [openai/whisper-large-v3](https://huggingface.co./openai/whisper-large-v3) and 🤗 Transformers to transcribe audio files\"\n",
" \" of arbitrary length.\"\n",
" ),\n",
" allow_flagging=\"never\",\n",
")\n",
"\n",
"demo.launch()\n"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 648
},
"id": "K0b2UZLVdIze",
"outputId": "bcff00e0-4fc8-4883-9ba4-480f5a6665f0"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
"\n",
"Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
"Running on public URL: https://037dbdb04542aa1a29.gradio.live\n",
"\n",
"This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co./spaces)\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"<IPython.core.display.HTML object>"
],
"text/html": [
"<div><iframe src=\"https://037dbdb04542aa1a29.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
]
},
"metadata": {}
},
{
"output_type": "execute_result",
"data": {
"text/plain": []
},
"metadata": {},
"execution_count": 4
}
]
}
]
} |