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"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
""
]
},
{
"cell_type": "markdown",
"source": [
"## Install"
],
"metadata": {
"id": "NO47mAC5iGH7"
}
},
{
"cell_type": "code",
"source": [
"# install bark (make sure you have torch>=2 for much faster flash-attention)\n",
"!pip install git+https://github.com/suno-ai/bark.git"
],
"metadata": {
"id": "YkizeTpG_3T7",
"colab": {
"base_uri": "https://localhost:8080/"
},
"outputId": "56457dd9-67f1-44ee-d6b6-2fdfa95d0ae5"
},
"execution_count": 1,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Collecting git+https://github.com/suno-ai/bark.git\n",
" Cloning https://github.com/suno-ai/bark.git to /tmp/pip-req-build-083hdi07\n",
" Running command git clone --filter=blob:none --quiet https://github.com/suno-ai/bark.git /tmp/pip-req-build-083hdi07\n",
" Resolved https://github.com/suno-ai/bark.git to commit f4f32d4cd480dfec1c245d258174bc9bde3c2148\n",
" Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
" Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
" Installing backend dependencies ... \u001b[?25l\u001b[?25hdone\n",
" Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
"Collecting boto3 (from suno-bark==0.0.1a0)\n",
" Downloading boto3-1.34.122-py3-none-any.whl (139 kB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m139.3/139.3 kB\u001b[0m \u001b[31m3.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hCollecting encodec (from suno-bark==0.0.1a0)\n",
" Downloading encodec-0.1.1.tar.gz (3.7 MB)\n",
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"\u001b[?25h Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
"Collecting funcy (from suno-bark==0.0.1a0)\n",
" Downloading funcy-2.0-py2.py3-none-any.whl (30 kB)\n",
"Requirement already satisfied: huggingface-hub>=0.14.1 in /usr/local/lib/python3.10/dist-packages (from suno-bark==0.0.1a0) (0.23.2)\n",
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"Requirement already satisfied: tokenizers in /usr/local/lib/python3.10/dist-packages (from suno-bark==0.0.1a0) (0.19.1)\n",
"Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (from suno-bark==0.0.1a0) (2.3.0+cu121)\n",
"Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from suno-bark==0.0.1a0) (4.66.4)\n",
"Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (from suno-bark==0.0.1a0) (4.41.2)\n",
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"Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.14.1->suno-bark==0.0.1a0) (2023.6.0)\n",
"Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.14.1->suno-bark==0.0.1a0) (24.0)\n",
"Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.14.1->suno-bark==0.0.1a0) (6.0.1)\n",
"Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.14.1->suno-bark==0.0.1a0) (2.31.0)\n",
"Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.14.1->suno-bark==0.0.1a0) (4.12.1)\n",
"Collecting botocore<1.35.0,>=1.34.122 (from boto3->suno-bark==0.0.1a0)\n",
" Downloading botocore-1.34.122-py3-none-any.whl (12.3 MB)\n",
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"\u001b[?25hCollecting jmespath<2.0.0,>=0.7.1 (from boto3->suno-bark==0.0.1a0)\n",
" Downloading jmespath-1.0.1-py3-none-any.whl (20 kB)\n",
"Collecting s3transfer<0.11.0,>=0.10.0 (from boto3->suno-bark==0.0.1a0)\n",
" Downloading s3transfer-0.10.1-py3-none-any.whl (82 kB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m82.2/82.2 kB\u001b[0m \u001b[31m12.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hRequirement already satisfied: torchaudio in /usr/local/lib/python3.10/dist-packages (from encodec->suno-bark==0.0.1a0) (2.3.0+cu121)\n",
"Collecting einops (from encodec->suno-bark==0.0.1a0)\n",
" Downloading einops-0.8.0-py3-none-any.whl (43 kB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m43.2/43.2 kB\u001b[0m \u001b[31m6.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hRequirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch->suno-bark==0.0.1a0) (1.12.1)\n",
"Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch->suno-bark==0.0.1a0) (3.3)\n",
"Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch->suno-bark==0.0.1a0) (3.1.4)\n",
"Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch->suno-bark==0.0.1a0)\n",
" Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n",
"Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch->suno-bark==0.0.1a0)\n",
" Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)\n",
"Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch->suno-bark==0.0.1a0)\n",
" Using cached nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)\n",
"Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch->suno-bark==0.0.1a0)\n",
" Using cached nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)\n",
"Collecting nvidia-cublas-cu12==12.1.3.1 (from torch->suno-bark==0.0.1a0)\n",
" Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n",
"Collecting nvidia-cufft-cu12==11.0.2.54 (from torch->suno-bark==0.0.1a0)\n",
" Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)\n",
"Collecting nvidia-curand-cu12==10.3.2.106 (from torch->suno-bark==0.0.1a0)\n",
" Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n",
"Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch->suno-bark==0.0.1a0)\n",
" Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n",
"Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch->suno-bark==0.0.1a0)\n",
" Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n",
"Collecting nvidia-nccl-cu12==2.20.5 (from torch->suno-bark==0.0.1a0)\n",
" Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl (176.2 MB)\n",
"Collecting nvidia-nvtx-cu12==12.1.105 (from torch->suno-bark==0.0.1a0)\n",
" Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n",
"Requirement already satisfied: triton==2.3.0 in /usr/local/lib/python3.10/dist-packages (from torch->suno-bark==0.0.1a0) (2.3.0)\n",
"Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch->suno-bark==0.0.1a0)\n",
" Downloading nvidia_nvjitlink_cu12-12.5.40-py3-none-manylinux2014_x86_64.whl (21.3 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.3/21.3 MB\u001b[0m \u001b[31m44.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
"\u001b[?25hRequirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers->suno-bark==0.0.1a0) (2024.5.15)\n",
"Requirement already satisfied: safetensors>=0.4.1 in /usr/local/lib/python3.10/dist-packages (from transformers->suno-bark==0.0.1a0) (0.4.3)\n",
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"Requirement already satisfied: urllib3!=2.2.0,<3,>=1.25.4 in /usr/local/lib/python3.10/dist-packages (from botocore<1.35.0,>=1.34.122->boto3->suno-bark==0.0.1a0) (2.0.7)\n",
"Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch->suno-bark==0.0.1a0) (2.1.5)\n",
"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.14.1->suno-bark==0.0.1a0) (3.3.2)\n",
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.14.1->suno-bark==0.0.1a0) (3.7)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.14.1->suno-bark==0.0.1a0) (2024.6.2)\n",
"Requirement already satisfied: mpmath<1.4.0,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy->torch->suno-bark==0.0.1a0) (1.3.0)\n",
"Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil<3.0.0,>=2.1->botocore<1.35.0,>=1.34.122->boto3->suno-bark==0.0.1a0) (1.16.0)\n",
"Building wheels for collected packages: suno-bark, encodec\n",
" Building wheel for suno-bark (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for suno-bark: filename=suno_bark-0.0.1a0-py3-none-any.whl size=2567358 sha256=2270d76114b325bf7309b76a7e064066121456742c401d877d847eaa4999b507\n",
" Stored in directory: /tmp/pip-ephem-wheel-cache-l6h9fkbb/wheels/e6/6d/c2/107ed849afe600f905bb4049a026df3c7c5aa75d86c2721ec7\n",
" Building wheel for encodec (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
" Created wheel for encodec: filename=encodec-0.1.1-py3-none-any.whl size=45762 sha256=8664c39d36e420a024f02bd4af61fdcb6308e6786919f7c9277bdd52f006ba3f\n",
" Stored in directory: /root/.cache/pip/wheels/fc/36/cb/81af8b985a5f5e0815312d5e52b41263237af07b977e6bcbf3\n",
"Successfully built suno-bark encodec\n",
"Installing collected packages: funcy, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, jmespath, einops, nvidia-cusparse-cu12, nvidia-cudnn-cu12, botocore, s3transfer, nvidia-cusolver-cu12, boto3, encodec, suno-bark\n",
"Successfully installed boto3-1.34.122 botocore-1.34.122 einops-0.8.0 encodec-0.1.1 funcy-2.0 jmespath-1.0.1 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.40 nvidia-nvtx-cu12-12.1.105 s3transfer-0.10.1 suno-bark-0.0.1a0\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"## Basics"
],
"metadata": {
"id": "7Ge31CAciLNJ"
}
},
{
"cell_type": "code",
"source": [
"from bark import SAMPLE_RATE, generate_audio, preload_models\n",
"from IPython.display import Audio\n",
"preload_models()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 469,
"referenced_widgets": [
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]
},
"id": "t9Vlr3RRt6B9",
"outputId": "eebaa2a8-35f3-43ae-a4b4-9a2ee8a4897c"
},
"execution_count": 2,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n",
"The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
"To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
"You will be able to reuse this secret in all of your notebooks.\n",
"Please note that authentication is recommended but still optional to access public models or datasets.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"text_2.pt: 0%| | 0.00/5.35G [00:00, ?B/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "536d3bc03f9c4808a9bb3e595a7a7f4c"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"tokenizer_config.json: 0%| | 0.00/49.0 [00:00, ?B/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "618047084f864d4289ffad26935e5548"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"vocab.txt: 0%| | 0.00/996k [00:00, ?B/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "827870d54e1c4d749c97fdafaef15a4d"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"tokenizer.json: 0%| | 0.00/1.96M [00:00, ?B/s]"
],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
"version_minor": 0,
"model_id": "32da05c443054983bd046bdca1803885"
}
},
"metadata": {}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.10/dist-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
" warnings.warn(\n"
]
},
{
"output_type": "display_data",
"data": {
"text/plain": [
"config.json: 0%| | 0.00/625 [00:00, ?B/s]"
],
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"version_major": 2,
"version_minor": 0,
"model_id": "5ca4fee421b045158e5f47a496da7600"
}
},
"metadata": {}
},
{
"output_type": "display_data",
"data": {
"text/plain": [
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],
"application/vnd.jupyter.widget-view+json": {
"version_major": 2,
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}
},
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},
{
"output_type": "display_data",
"data": {
"text/plain": [
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],
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"version_major": 2,
"version_minor": 0,
"model_id": "3a0b324e27a3434d99e514e17db71f38"
}
},
"metadata": {}
},
{
"output_type": "stream",
"name": "stderr",
"text": [
"/usr/local/lib/python3.10/dist-packages/torch/nn/utils/weight_norm.py:28: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\n",
" warnings.warn(\"torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.\")\n",
"Downloading: \"https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th\" to /root/.cache/torch/hub/checkpoints/encodec_24khz-d7cc33bc.th\n",
"100%|██████████| 88.9M/88.9M [00:01<00:00, 61.6MB/s]\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"# 0 : 기본 여성 목소리\n",
"# 6 : 중후한 교수님\n",
"# 7 : 걸걸한 교수님\n",
"# 8 : 나이 많으신 교수님\n",
"# 9 : 스프치 강사\n",
"number = 7 # 0 ~ 9\n",
"text_prompt = \"\"\"\n",
" 여러분의 제품에 API를 연동해 보고 싶으신가요?\n",
"\"\"\"\n",
"# text_prompt = \"250쿼리를 제공 합니다.\" # Good : 1, 4\n",
"# https://github.com/suno-ai/bark/issues/380#issuecomment-1625127198\n",
"audio_array = generate_audio(text_prompt, history_prompt=f\"v2/ko_speaker_{number}\")\n",
"Audio(audio_array, rate=SAMPLE_RATE)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 95
},
"id": "ZpcKjG7AOT_p",
"outputId": "f12c855b-971b-402b-9685-62650b5f2069"
},
"execution_count": 22,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"100%|██████████| 227/227 [00:03<00:00, 66.00it/s]\n",
"100%|██████████| 12/12 [00:16<00:00, 1.36s/it]\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
""
],
"text/html": [
"\n",
" \n",
" "
]
},
"metadata": {},
"execution_count": 22
}
]
},
{
"cell_type": "code",
"source": [
"number = 0 # 0 ~ 9\n",
"text_prompt = \"\"\"\n",
" 여러분의 제품에 API를 연동해 보고 싶으신가요?\n",
"\"\"\"\n",
"# text_prompt = \"250쿼리를 제공 합니다.\" # Good : 1, 4\n",
"# https://github.com/suno-ai/bark/issues/380#issuecomment-1625127198\n",
"audio_array = generate_audio(text_prompt, history_prompt=f\"v2/ko_speaker_{number}\")\n",
"Audio(audio_array, rate=SAMPLE_RATE)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 95
},
"id": "bbBBzNaiWCN2",
"outputId": "22282039-69b2-4fbd-ff43-8abc17498e5b"
},
"execution_count": 25,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"100%|██████████| 212/212 [00:03<00:00, 58.62it/s]\n",
"100%|██████████| 11/11 [00:11<00:00, 1.04s/it]\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
""
],
"text/html": [
"\n",
" \n",
" "
]
},
"metadata": {},
"execution_count": 25
}
]
},
{
"cell_type": "code",
"source": [
"number = 9 # 0 ~ 9\n",
"text_prompt = \"\"\"\n",
" 여러분의 제품에 API를 연동해 보고 싶으신가요?\n",
"\"\"\"\n",
"# text_prompt = \"250쿼리를 제공 합니다.\" # Good : 1, 4\n",
"# https://github.com/suno-ai/bark/issues/380#issuecomment-1625127198\n",
"audio_array = generate_audio(text_prompt, history_prompt=f\"v2/ko_speaker_{number}\")\n",
"Audio(audio_array, rate=SAMPLE_RATE)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 95
},
"id": "ckLaM4uSWG62",
"outputId": "50b90b51-4c6d-457f-85ae-56bfc4ff2109"
},
"execution_count": 24,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"100%|██████████| 208/208 [00:03<00:00, 67.32it/s]\n",
"100%|██████████| 11/11 [00:15<00:00, 1.39s/it]\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
""
],
"text/html": [
"\n",
" \n",
" "
]
},
"metadata": {},
"execution_count": 24
}
]
},
{
"cell_type": "code",
"source": [
"text_prompt = \"\"\"\n",
" Hello, my name is Suno. And, uh — and I like pizza. [laughs]\n",
" But I also have other interests such as playing tic tac toe.\n",
"\"\"\"\n",
"audio_array = generate_audio(text_prompt)\n",
"Audio(audio_array, rate=SAMPLE_RATE)"
],
"metadata": {
"id": "NyYQ--3YksJY",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 111
},
"outputId": "ec740a8b-6bb4-4f14-f083-da2b5a426ece"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"100%|██████████| 100/100 [00:52<00:00, 1.91it/s]\n",
"100%|██████████| 26/26 [03:53<00:00, 8.98s/it]\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
""
],
"text/html": [
"\n",
" \n",
" "
]
},
"metadata": {},
"execution_count": 4
}
]
},
{
"cell_type": "markdown",
"source": [
"## Advanced examples"
],
"metadata": {
"id": "b5rDDPxrRAKa"
}
},
{
"cell_type": "code",
"source": [
"text_prompt = \"\"\"\n",
" Buenos días Miguel. Tu colega piensa que tu alemán es extremadamente malo.\n",
" But I suppose your english isn't terrible.\n",
"\"\"\"\n",
"audio_array = generate_audio(text_prompt)\n",
"Audio(audio_array, rate=SAMPLE_RATE)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 111
},
"id": "RnYiRaffReIW",
"outputId": "3a24bed0-1b4b-411b-a20b-1980a5a02ea9"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"100%|██████████| 100/100 [01:01<00:00, 1.63it/s]\n",
"100%|██████████| 29/29 [04:41<00:00, 9.71s/it]\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
""
],
"text/html": [
"\n",
" \n",
" "
]
},
"metadata": {},
"execution_count": 4
}
]
},
{
"cell_type": "code",
"source": [
"text_prompt = \"\"\"\n",
" WOMAN: I would like an oatmilk latte please.\n",
" MAN: Wow, that's expensive!\n",
"\"\"\"\n",
"audio_array = generate_audio(text_prompt)\n",
"Audio(audio_array, rate=SAMPLE_RATE)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 111
},
"id": "y2XOBRFhReDy",
"outputId": "0b450630-64b7-4dd5-a0e3-9bd442dce6fa"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"100%|██████████| 100/100 [00:31<00:00, 3.20it/s]\n",
"100%|██████████| 17/17 [02:29<00:00, 8.82s/it]\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
""
],
"text/html": [
"\n",
" \n",
" "
]
},
"metadata": {},
"execution_count": 5
}
]
},
{
"cell_type": "code",
"source": [
"text_prompt = \"\"\"\n",
" I have a silky smooth voice, and today I will tell you\n",
" about the exercise regimen of the common sloth.\n",
"\"\"\"\n",
"audio_array = generate_audio(text_prompt, history_prompt=\"v2/en_speaker_1\")\n",
"Audio(audio_array, rate=SAMPLE_RATE)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 111
},
"id": "6p153cqEmXLA",
"outputId": "bae8f498-6129-4c66-b0b4-78f1fa2463cb"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stderr",
"text": [
"100%|██████████| 100/100 [00:30<00:00, 3.23it/s]\n",
"100%|██████████| 19/19 [03:29<00:00, 11.05s/it]\n"
]
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
""
],
"text/html": [
"\n",
" \n",
" "
]
},
"metadata": {},
"execution_count": 17
}
]
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "Cl01EACYRdgy"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [],
"metadata": {
"id": "qGSEorjKkr4u"
},
"execution_count": null,
"outputs": []
}
]
}