--- title: bark app_file: bark_webui.py sdk: gradio sdk_version: 3.39.0 --- # ๐Ÿš€ BARK INFINITY, Voices are Just Sounds. ๐ŸŽถ ๐ŸŒˆโœจ๐Ÿš€ #### Why this fork ? I do not have a GPU so I need Google Colab for running the python code, as there are notebooks available in this project my focus is here. [![Open In Colab](https://tinyurl.com/3m5bcd9h)](https://colab.research.google.com/github/steinhaug/bark-infinity/blob/main/notebooks/Bark-Infinity.ipynb) [![Open In Colab](https://tinyurl.com/jjbfsbk2)](https://colab.research.google.com/github/steinhaug/bark-infinity/blob/main/notebooks/Bark_Infinity_Long_Form_Audio_Colab.ipynb)



# ๐ŸŽ‰ Bark INFINITY Automatic Windows Installer, NVIDIA (CPU update soon) ๐ŸŽ‰ ### โš ๏ธ Note: make sure you fully extract the .zip file before running the .bat files. Check this image if you aren't sure: [install_help.PNG](https://raw.githubusercontent.com/JonathanFly/bark/main/one-click-bark-installer/install_help.PNG) ## Install Prerequisites: 1. **Just the regular Windows NVIDIA drivers**. You don't need anything else installed ahead of time. Not Pytorch. Nothing with `Cuda` in the name. Not even Python. In fact if you installed anything on your Windows system without using a venv or conda, it may cause a problem. 2. *(Optional But Recommended)* The Windows Terminal https://apps.microsoft.com/store/detail/windows-terminal/9N0DX20HK701 -- Bark still has a lot of text output and it's looks nicer and is easier to read in the Windows Terminal. But you can also use the regular Windows Command Prompt. ## Install Steps 1. Download the latest zip file from the releases page: https://github.com/JonathanFly/bark/releases 2. Extract the zip file into a directory. Choose a place where Bark will be installed. You will unzip about six small files. 3. Click on `INSTALL_bark_infinity_windows.bat` (you should not need to be administrator) 4. If the install finished with no errors, close that terminal window. Close any other open command line windows as well. 5. Click `LAUNCH_already_installed_bark_infinity_windows.bat` ## Install Problems 1. If you get a Windows permissions error, I seemed to get it randomly. Just trying again usually fixed it. You don't even need to restart from scratch, just rerun the script that threw the error. ### Command Line: Click `TROUBLESHOOT_bark_setup_manually_by_entering_the_conda_environment.bat` ``` cd bark python bark_perform.py python bark_perform.py --help ``` ### Trouble Shooting: Click `TROUBLESHOOT_bark_setup_manually_by_entering_the_conda_environment.bat` ``` -----Manual Updates----- Type `conda update -y -n base conda` to update conda. Type `conda update -y --all --solver=libmamba` to update all packages. Type `conda clean --all` to free up disk space from unused versions. Type `ffdl install -U --add-path` to try to fix ffmpeg not not problems. Type `pip install -r requirements-extra.txt` to try to manually install pip requirements. Type `conda env update -y -f environment-cuda-installer.yml --prune --solver=libmamba` to update your env manually, if the .yml changed. Type `cd bark` to enter the bark directory and then `git pull` to update the repo code. Type `git branch` to view branches and then Type `git checkout ` to switch branches. (You can try `git checkout bark_amd_directml_test` branch if you have an AMD GPU) -----Still Not Working?----- Go ahead and @ me on Bark Official Discord, username "Jonathan Fly" jonathanfly. Don't worry about waking me up with a message, my Discord never makes audible alerts. -----How do I get out of here?----- Type 'conda deactivate' to exit this environment and go back to normal terminal. ``` ![LAUNCH_already_installed_bark_infinity_windows.bat](https://github.com/JonathanFly/bark/assets/163408/fcd91d15-6bee-44c7-8c99-95ca48fbc1d5) # ๐ŸŽ‰ Pytorch 2.0 Bark AMD Install Test Pytorch 2.0 ๐ŸŽ‰ **DirectML works on AMD in Pytorch 2.0 Confirmed works.** It's not super fast but it's a lot faster than CPU. Bark AMD DirectML Instructions. What is DirectML? https://learn.microsoft.com/en-us/windows/ai/directml/gpu-pytorch-windows Install Miniconda. https://repo.anaconda.com/miniconda/Miniconda3-py310_23.3.1-0-Windows-x86_64.exe Then go to start menu and start a new "Ananconda Prompt" not regular windows command line ``` conda update -y conda conda update -y -n base conda conda install -y -n base conda-libmamba-solver conda create --name pydml_torch2 -y python=3.10.6 conda activate pydml_torch2 ``` make sure you see (pydml_torch2) in the corner of of your prompt. ***(pydml_torch2) C:\Users\YourName*** ``` conda install -y pip git --solver=libmamba conda update -y --all --solver=libmamba pip install ffmpeg_downloader ffdl install -U --add-path ``` Now quit out of the terminal and restart. We need ffmpeg in the path, which means you need to be able to type `ffmpeg -version` and have it work. If you close and restart, you should be able to do that. So close the terminal, close all window command lines or terminals to be sure. Then go back start menu and start a new "Ananaconda Prompt". This should be same you started the install. ``` conda activate pydml_torch2 ``` make sure you see (pydml_torch2) in the corner again. ***(pydml_torch2) C:\Users\YourName*** etc. Now try typing ``` ffmpeg -version ``` Do you see ffmpeg 6.0? If it doesn't work you can keep going and you can use .wav file outputs, and fix it later. Now the big conda install command. This could take 5 to 15 minutes, and if you have a slow internet it could even take hours, because it downloads multiple gigabytes. So if looks like it's frozen, let it go. Check your task manager and see if it's downloading. ### For testing torch 2.0, just some giant pip installs: ``` pip install torch==2.0.0 torchvision==0.15.1 torch-directml==0.2.0.dev230426 opencv-python torchvision==0.15.1 wget torch-directml==0.2.0.dev230426 pygments numpy pandas tensorboard matplotlib tqdm pyyaml boto3 funcy torchaudio transformers pydub pathvalidate rich nltk chardet av hydra-core>=1.1 einops scipy num2words pywin32 ffmpeg ffmpeg-python sentencepiece spacy==3.5.2 librosa jsonschema pytorch_lightning==1.9.4 pip install encodec flashy>=0.0.1 audiolm_pytorch==1.1.4 demucs pip install universal-startfile hydra_colorlog julius soundfile==0.12.1 gradio>=3.35.2 rich_argparse flashy>=0.0.1 ffmpeg_downloader rich_argparse devtools vector_quantize_pytorch pip install https://github.com/Sharrnah/fairseq/releases/download/v0.12.4/fairseq-0.12.4-cp310-cp310-win_amd64.whl `````` First set a SUNO_USE_DIRECTML variable. This tells Bark to use DirectML. If this doesn't work you can edit `/bark_infinity/config.py`` and set `SUNO_USE_DIRECTML`` to `True`` in the `DEFAULTS`` section. ``` set SUNO_USE_DIRECTML=1 ``` Download Bark: ``` git clone https://github.com/JonathanFly/bark.git cd bark ``` Change to the AMD Test Version ``` git checkout bark_amd_directml_test ``` Now try running it. Bark has to download all the models the first time it runs, so it might look frozen for awhile. It's another 10 gigs of files. ``` python bark_perform.py ``` When I tested this install, `bark_perform.py` seemed to freeze at downloading models without making progress. I don't know if was a fluke, but I ran `python bark_webui.py` and it downloaded them fine. Start the Bark UI ``` python bark_webui.py ``` Things that don't work: 1. Voice Cloning (might work?) 2. Top_k and top_p 3. Probably more things I haven't tested. ### Start Back UI Later 1. Click Anaconda Prompt in start menu 2. `conda activate pydml_torch2` 3. cd bark 4. `python bark_webui.py` ### Make it faster? (Note for later, don't try yet) 1. Install MKL exe https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl-download.html ``` conda install -y mkl mkl-service mkl_fft libcblas liblapacke liblapack blas-devel mkl-include mkl_random mkl-devel mkl-include libblas=*=*mkl mkl-static intel-openmp blas=*=*mkl -c intel -c conda-forge --solver=libmamba ``` # ๐Ÿนโ†—๏ธ This AMD Pytorch 1.13.1 (slower) ``` conda update -y conda conda update -y -n base conda conda install -y -n base conda-libmamba-solver conda create --name pydml -y python=3.10.6 conda activate pydml ``` make sure you see (pydml) in the corner of of your prompt. ***(pydml) C:\Users\YourName*** ``` conda install -y pip git --solver=libmamba conda update -y --all --solver=libmamba pip install ffmpeg_downloader ffdl install -U --add-path ``` Now quit out of the terminal and restart. We need ffmpeg in the path, which means you need to be able to type `ffmpeg -version` and have it work. If you close and restart, you should be able to do that. So close the terminal, close all window command lines or terminals to be sure. Then go back start menu and start a new "Ananaconda Prompt". This should be same you started the install. ``` conda activate pydml ``` make sure you see (pydml) in the corner again. ***(pydml) C:\Users\YourName*** etc. Now try typing ``` ffmpeg -version ``` Do you see ffmpeg 6.0? If it doesn't work you can keep going and you can use .wav file outputs, and fix it later. Now the big conda install command. This could take 5 to 15 minutes, and if you have a slow internet it could even take hours, because it downloads multiple gigabytes. So if looks like it's frozen, let it go. Check your task manager and see if it's downloading. ``` conda install -y pytorch==1.13.1 pygments numpy pandas tensorboard matplotlib tqdm pyyaml boto3 funcy torchvision==0.14.1 torchaudio==0.13.1 cpuonly transformers pydub pathvalidate rich nltk chardet av hydra-core>=1.1 einops scipy num2words pywin32 ffmpeg ffmpeg-python sentencepiece spacy==3.5.2 librosa jsonschema -c pytorch -c conda-forge --solver=libmamba ``` Now that's done a few more things we need, that are not in conda. So we have to use pip. This is where the instal can go wrong up. **We don't want anything to upgrade either torch or torchaudio to torch 2.0**, and it often happens by accident. (As far I know AMD DirectML Windows only works in Torch 1.13, not 2.0. If anyone knows different let me know!) If you somehow end up installing torch 2.0. Try `pip uninstall torch torchaudio` and then redo the big long conda install command (the one with `pytorch==1.13.1` in it). ``` pip install universal-startfile hydra_colorlog julius soundfile==0.12.1 gradio>=3.35.2 rich_argparse flashy>=0.0.1 ffmpeg_downloader rich_argparse devtools ``` ``` pip install encodec flashy>=0.0.1 audiolm_pytorch==1.1.4 demucs --no-dependencies pip install https://github.com/Sharrnah/fairseq/releases/download/v0.12.4/fairseq-0.12.4-cp310-cp310-win_amd64.whl --no-dependencies ``` And now finally the actual `torch-directml` that has GPU support. I found installing this last seems best, but you could try doing it earlier. ``` pip install torch-directml==0.1.13.1.dev230413 ``` If everything worked, you might be done. Now we install Bark. And then run one command line test first with bark_perform.py First set a SUNO_USE_DIRECTML variable. This tells Bark to use DirectML. If this doesn't work you can edit `/bark_infinity/config.py`` and set `SUNO_USE_DIRECTML`` to `True`` in the `DEFAULTS`` section. ``` set SUNO_USE_DIRECTML=1 ``` Download Bark: ``` git clone https://github.com/JonathanFly/bark.git cd bark ``` Change to the AMD Test Version ``` git checkout bark_amd_directml_test ``` Now try running it. Bark has to download all the models the first time it runs, so it might look frozen for awhile. It's another 10 gigs of files. ``` python bark_perform.py ``` When I tested this install, `bark_perform.py` seemed to freeze at downloading models without making progress. I don't know if was a fluke, but I ran `python bark_webui.py` and it downloaded them fine. Start the Bark UI ``` python bark_webui.py ``` Things that don't work: 1. Voice Cloning 2. Top_k and top_p 3. Probably more things I haven't tested. ### Start Back UI Later 1. Click Anaconda Prompt in start menu 2. `conda activate pydml` 3. cd bark 4. `python bark_webui.py` ### Make it faster? (Note for later, don't try yet) 1. Install MKL exe https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl-download.html ``` conda install -y mkl mkl-service mkl_fft libcblas liblapacke liblapack blas-devel mkl-include mkl_random mkl-devel mkl-include libblas=*=*mkl mkl-static intel-openmp blas=*=*mkl -c intel -c conda-forge --solver=libmamba ``` โšก Low GPU memory? No problem. CPU offloading. โšก Somewhat easy install? # ๐ŸŽ‰ Install Bark Infinity Any OS With Mamba (or Conda) ๐ŸŽ‰ ## Mamba Install (Still Works) (Should work...) (Mamba is a fast version of conda. They should work the same if you install either one, just change mamba to conda or vice-versa.) Pip and conda/mamba are two _different_ ways of installing Bark Infinity. If you use **Mamba** do not install anything. Don't install _pytorch_, do not install anything with 'CUDA' in the same. You don't need to lookup a YouTube tutorial. Just type the commands. The only thing you need installed is the NVIDIA drivers. **Take note of which lines are for NVIDIA or CPU, or Linux or Windows.** There is one exception, on Windows if you don't have the better Windows Terminal installed, that is a nice to have feature https://apps.microsoft.com/store/detail/windows-terminal/9N0DX20HK701 You don't have to but it may display the output from the bark commands better. When you start **Anaconda Prompt (miniconda3)** you can do it from the new Windows Terminal app, clicking on the down arrow next to the plus, should let you pick **Anaconda Prompt (miniconda3)** 1. Go here: [https://github.com/conda-forge/miniforge#mambaforge](https://github.com/conda-forge/miniforge#mambaforge) 2. 3. Download a **Python 3.10 Miniconda3** installer for your OS. Windows 64-bit, macOS, and Linux probably don't need a guide. a. Install the **Mambaforge** for your OS, not specifically Windows. OSX for OSX etc. b. Don't install Mambaforge-pypy3. (It probably works fine, it is just not what I tested.) Install the one above that, just plain **Mambaforge**. Or you can use **Conda**, Mamba should faster but sometimes Conda may be more compatible. 1. Install the **Python 3.10 Miniconda3** exe. Then start the miniforge **'Miniforge Prompt** Terminal which is a new program it installed. You will always use this program for Bark. 2. Start **'Miniforge Prompt** Be careful not to start the regular windows command line. (Unless you installed the new Terminal and know how to switch.) It should say **"Anaconda Prompt (miniconda3)**" You should see also terminal that says "**(base)**". ### Do not move forward until you see _(base)_. 5. **Choose the place to install Bark Infinity directory.** You can also just leave it at default. If you make a LOT of audio you think about a place with a lot of space. When you start **"Anaconda Prompt (miniconda3)"** you will be in a directory, in Windows, probably something like** "C:\Users\YourName"**. Okay to install there. Just remember where you put it. It will be in **/bark.** (If you already had bark-infinity installed and want to update instead of reinstalling, skip to the end.) 6. Type the next commands _exactly_. Hit "Y" for yes where you need to: ``` mamba update -y mamba mamba create --name bark-infinity python=3.10 mamba activate bark-infinity ## NVIDIA GPU ONLY mamba install -y -k cuda ninja git pip -c nvidia/label/cuda-11.7.0 -c nvidia pip install torch==2.0.1+cu117 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117 ## END NVIDIA GPU ONLY ## CPU ONLY, Or MacOS mamba install -y -k ninja git pip install torch torchvision torchaudio ## END CPU ONLY, Or MacOS ## WINDOWS ONLY fairseq pip install fairseq@https://github.com/Sharrnah/fairseq/releases/download/v0.12.4/fairseq-0.12.4-cp310-cp310-win_amd64.whl ## NON-WINDOWS fairseq mamba install fairseq pip install audiolm_pytorch==1.1.4 --no-deps git clone https://github.com/JonathanFly/bark.git cd bark pip install -r barki-allpip.txt --upgrade ffdl install -U --add-path ``` # Run Bark Infinity ## Run command line version ``` python bark_perform.py ``` ## Run web ui version ``` python bark_webui.py ``` (If you see a warning that "No GPU being used. Careful, inference might be very slow!" after `python bark_perform.py` then something may be wrong, if you have GPU. If you *don't* see that then the GPU is working.) # Start Bark Infinity At A Later Time To restart later, start **Miniforge Prompt.** Not Regular Prompt. Make sure you see (base) You will type a command to activate **bark-infinity** and of base, like this: ``` mamba activate bark-infinity cd bark python bark_webui.py ``` # Update Bark Infinity ``` git pull pip install -r barki-allpip.txt --upgrade ``` I have so much good Bark I need to post at [twitter.com/jonathanfly](https://twitter.com/jonathanfly) # ๐ŸŒ  The Past: ๐ŸŒ  Bark Infinity started as a humble ๐Ÿ’ป command line wrapper, a CLI ๐Ÿ’ฌ. Built from simple keyword commands, it was a proof of concept ๐Ÿงช, a glimmer of potential ๐Ÿ’ก. # ๐ŸŒŸ The Present: ๐ŸŒŸ Bark Infinity _evolved_ ๐Ÿงฌ, expanding across dimensions ๐ŸŒ. Infinite Length ๐ŸŽต๐Ÿ”„, Infinite Voices ๐Ÿ”Š๐ŸŒˆ, and a true high point in human history: [๐ŸŒ Infinite Awkwardness ๐Ÿ•บ](https://twitter.com/jonathanfly/status/1650001584485552130). But for some people, the time-tested command line interface was not a good fit. Many couldn't even try Bark ๐Ÿ˜ž, struggling with CUDA gods ๐ŸŒฉ and being left with cryptic error messages ๐Ÿง and a chaotic computer ๐Ÿ’พ. Many people felt veryโ€ฆ UN INFINITE. # ๐Ÿ”œ๐Ÿš€ The Future: ๐Ÿš€ ๐Ÿš€ Bark Infinity ๐Ÿพ was born in the command line, and Bark Infinity grew within the command line. We live in the era where old fashioned command line applications are wrapped in โœจfancy Gradio Uis๐ŸŒˆ and ๐Ÿ–ฑ๏ธOne Click Installers. We all must adapt to a changing world, right? *Or do we?* ## ๐ŸŒŸ (OLD NOT UPDATED) README ๐ŸŒŸ __ ### 1. INFINITY VOICES ๐Ÿ”Š๐ŸŒˆ Discover cool new voices and reuse them. Performers, musicians, sound effects, two party dialog scenes. Save and share them. Every audio clip saves a speaker.npz file with the voice. To reuse a voice, move the generated speaker.npz file (named the same as the .wav file) to the "prompts" directory inside "bark" where all the other .npz files are. ๐Ÿ”Š With random celebrity appearances! (I accidentally left a bunch of voices in the repo, some of them are pretty good. Use --history_prompt 'en_fiery' for the same voice as the audio sample right after this sentence.) https://user-images.githubusercontent.com/163408/233747981-173b5f03-654e-4a0e-b71b-5d220601fcc7.mp4 ### 2. INFINITY LENGTH ๐ŸŽต๐Ÿ”„ Any length prompt and audio clips. Sometimes the final result is seamless, sometimes it's stable (but usually not both!). ๐ŸŽต Now with Slowly Morphing Rick Rolls! Can you even spot the seams in the most earnest Rick Rolls you've ever heard in your life? https://user-images.githubusercontent.com/163408/233747400-b18411f8-afcb-437d-9288-c54cc2c95e62.mp4 ### ๐Ÿ•บ Confused Travolta Mode ๐Ÿ•บ Confused Travolta GIF ![confused_travolta](https://user-images.githubusercontent.com/163408/233747428-c6bf03e2-b3ce-4ce3-a29d-836bf73a4ec2.gif) Can your text-to-speech model stammer and stall like a student answering a question about a book they didn't read? Bark can. That's the human touch. The *semantic* touch. You can almost feel the awkward silence through the screen. ## ๐Ÿ’ก But Wait, There's More: Travolta Mode Isn't Just A Joke ๐Ÿ’ก Are you tired of telling your TTS model what to say? Why not take a break and let your TTS model do the work for you. With enough patience and Confused Travolta Mode, Bark can finish your jokes for you. https://user-images.githubusercontent.com/163408/233746957-f3bbe25f-c8f0-4570-97b1-1005e1b40cbe.mp4 Truly we live in the future. It might take 50 tries to get a joke and it's probably an accident, but all 49 failures are also *very* amusing so it's a win/win. (That's right, I set a single function flag to False in a Bark and raved about the amazing new feature. Everything here is small potatoes really.) https://user-images.githubusercontent.com/163408/233746872-cac78447-8e87-49e7-b79b-28ec51264019.mp4 _**BARK INFINITY** is possible because Bark is such an amazingly simple and powerful model that even I could poke around easily._ _For music, I recommend using the --split_by_lines and making sure you use a multiline string as input. You'll generally get better results if you manually split your text, which I neglected to provide an easy way to do because I stayed too late listening to 100 different Bark versions of a scene an Andor and failed Why was 6 afraid of 7 jokes._ ## ๐Ÿ“ Command Line Options ๐Ÿ“ (Some of these parameters are not implemented.) Type --help or use the GUI ``` python bark_perform.py --help ``` ### prompt_file input text file example ```myprompts.txt This is the first prompt. Lots of text here maybe. As long as you want. AAAAA This is the second prompt. AAAAA This is the third prompt. ``` ``` python bark_perform.py --prompt_file myprompts.txt --split_input_into_separate_prompts_by string --split_input_into_separate_prompts_by_value AAAAA --output_dir myprompts_samples ``` # ๐Ÿถ Bark Original Readme ๐Ÿถ [![](https://dcbadge.vercel.app/api/server/J2B2vsjKuE?style=flat&compact=True)](https://discord.gg/J2B2vsjKuE) [![Twitter](https://img.shields.io/twitter/url/https/twitter.com/OnusFM.svg?style=social&label=@OnusFM)](https://twitter.com/OnusFM) [Examples](https://suno-ai.notion.site/Bark-Examples-5edae8b02a604b54a42244ba45ebc2e2) โ€ข [Suno Studio Waitlist](https://3os84zs17th.typeform.com/suno-studio) โ€ข [Updates](#-updates) โ€ข [How to Use](#-usage-in-python) โ€ข [Installation](#-installation) โ€ข [FAQ](#-faq) [//]:
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Bark is a transformer-based text-to-audio model created by [Suno](https://suno.ai). Bark can generate highly realistic, multilingual speech as well as other audio - including music, background noise and simple sound effects. The model can also produce nonverbal communications like laughing, sighing and crying. To support the research community, we are providing access to pretrained model checkpoints, which are ready for inference and available for commercial use. ## โš  Disclaimer Bark was developed for research purposes. It is not a conventional text-to-speech model but instead a fully generative text-to-audio model, which can deviate in unexpected ways from provided prompts. Suno does not take responsibility for any output generated. Use at your own risk, and please act responsibly. ## ๐ŸŽง Demos [![Open in Spaces](https://img.shields.io/badge/๐Ÿค—-Open%20in%20Spaces-blue.svg)](https://huggingface.co/spaces/suno/bark) [![Open on Replicate](https://img.shields.io/badge/ยฎ๏ธ-Open%20on%20Replicate-blue.svg)](https://replicate.com/suno-ai/bark) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1eJfA2XUa-mXwdMy7DoYKVYHI1iTd9Vkt?usp=sharing) ## ๐Ÿš€ Updates **2023.05.01** - ยฉ๏ธ Bark is now licensed under the MIT License, meaning it's now available for commercial use! - โšก 2x speed-up on GPU. 10x speed-up on CPU. We also added an option for a smaller version of Bark, which offers additional speed-up with the trade-off of slightly lower quality. - ๐Ÿ“• [Long-form generation](notebooks/long_form_generation.ipynb), voice consistency enhancements and other examples are now documented in a new [notebooks](./notebooks) section. - ๐Ÿ‘ฅ We created a [voice prompt library](https://suno-ai.notion.site/8b8e8749ed514b0cbf3f699013548683?v=bc67cff786b04b50b3ceb756fd05f68c). We hope this resource helps you find useful prompts for your use cases! You can also join us on [Discord](https://discord.gg/J2B2vsjKuE), where the community actively shares useful prompts in the **#audio-prompts** channel. - ๐Ÿ’ฌ Growing community support and access to new features here: [![](https://dcbadge.vercel.app/api/server/J2B2vsjKuE)](https://discord.gg/J2B2vsjKuE) - ๐Ÿ’พ You can now use Bark with GPUs that have low VRAM (<4GB). **2023.04.20** - ๐Ÿถ Bark release! ## ๐Ÿ Usage in Python

๐Ÿช‘ Basics

 ```python from bark import SAMPLE_RATE, generate_audio, preload_models from scipy.io.wavfile import write as write_wav from IPython.display import Audio # download and load all models preload_models() # generate audio from text text_prompt = """ Hello, my name is Suno. And, uh โ€” and I like pizza. [laughs] But I also have other interests such as playing tic tac toe. """ audio_array = generate_audio(text_prompt) # save audio to disk write_wav("bark_generation.wav", SAMPLE_RATE, audio_array) # play text in notebook Audio(audio_array, rate=SAMPLE_RATE) ``` [pizza.webm](https://user-images.githubusercontent.com/5068315/230490503-417e688d-5115-4eee-9550-b46a2b465ee3.webm)

๐ŸŒŽ Foreign Language
Bark supports various languages out-of-the-box and automatically determines language from input text. When prompted with code-switched text, Bark will attempt to employ the native accent for the respective languages. English quality is best for the time being, and we expect other languages to further improve with scaling.

```python text_prompt = """ ์ถ”์„์€ ๋‚ด๊ฐ€ ๊ฐ€์žฅ ์ข‹์•„ํ•˜๋Š” ๋ช…์ ˆ์ด๋‹ค. ๋‚˜๋Š” ๋ฉฐ์น  ๋™์•ˆ ํœด์‹์„ ์ทจํ•˜๊ณ  ์นœ๊ตฌ ๋ฐ ๊ฐ€์กฑ๊ณผ ์‹œ๊ฐ„์„ ๋ณด๋‚ผ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. """ audio_array = generate_audio(text_prompt) ``` [suno_korean.webm](https://user-images.githubusercontent.com/32879321/235313033-dc4477b9-2da0-4b94-9c8b-a8c2d8f5bb5e.webm) *Note: since Bark recognizes languages automatically from input text, it is possible to use for example a german history prompt with english text. This usually leads to english audio with a german accent.*

๐ŸŽถ Music

 Bark can generate all types of audio, and, in principle, doesn't see a difference between speech and music. Sometimes Bark chooses to generate text as music, but you can help it out by adding music notes around your lyrics.

```python text_prompt = """ โ™ช In the jungle, the mighty jungle, the lion barks tonight โ™ช """ audio_array = generate_audio(text_prompt) ``` [lion.webm](https://user-images.githubusercontent.com/5068315/230684766-97f5ea23-ad99-473c-924b-66b6fab24289.webm)

๐ŸŽค Voice Presets

 Bark supports 100+ speaker presets across [supported languages](#supported-languages). You can browse the library of speaker presets [here](https://suno-ai.notion.site/8b8e8749ed514b0cbf3f699013548683?v=bc67cff786b04b50b3ceb756fd05f68c), or in the [code](bark/assets/prompts). The community also often shares presets in [Discord](https://discord.gg/J2B2vsjKuE). Bark tries to match the tone, pitch, emotion and prosody of a given preset, but does not currently support custom voice cloning. The model also attempts to preserve music, ambient noise, etc.

```python text_prompt = """ I have a silky smooth voice, and today I will tell you about the exercise regimen of the common sloth. """ audio_array = generate_audio(text_prompt, history_prompt="v2/en_speaker_1") ``` [sloth.webm](https://user-images.githubusercontent.com/5068315/230684883-a344c619-a560-4ff5-8b99-b4463a34487b.webm)
### Generating Longer Audio By default, `generate_audio` works well with around 13 seconds of spoken text. For an example of how to do long-form generation, see this [example notebook](notebooks/long_form_generation.ipynb).
Click to toggle example long-form generations (from the example notebook) [dialog.webm](https://user-images.githubusercontent.com/2565833/235463539-f57608da-e4cb-4062-8771-148e29512b01.webm) [longform_advanced.webm](https://user-images.githubusercontent.com/2565833/235463547-1c0d8744-269b-43fe-9630-897ea5731652.webm) [longform_basic.webm](https://user-images.githubusercontent.com/2565833/235463559-87efe9f8-a2db-4d59-b764-57db83f95270.webm)
## ๐Ÿ’ป Installation ``` pip install git+https://github.com/suno-ai/bark.git ``` or ``` git clone https://github.com/suno-ai/bark cd bark && pip install . ``` *Note: Do NOT use 'pip install bark'. It installs a different package, which is not managed by Suno.* ## ๐Ÿ› ๏ธ Hardware and Inference Speed Bark has been tested and works on both CPU and GPU (`pytorch 2.0+`, CUDA 11.7 and CUDA 12.0). On enterprise GPUs and PyTorch nightly, Bark can generate audio in roughly real-time. On older GPUs, default colab, or CPU, inference time might be significantly slower. For older GPUs or CPU you might want to consider using smaller models. Details can be found in out tutorial sections here. The full version of Bark requires around 12GB of VRAM to hold everything on GPU at the same time. To use a smaller version of the models, which should fit into 8GB VRAM, set the environment flag `SUNO_USE_SMALL_MODELS=True`. If you don't have hardware available or if you want to play with bigger versions of our models, you can also sign up for early access to our model playground [here](https://3os84zs17th.typeform.com/suno-studio). ## โš™๏ธ Details Bark is fully generative tex-to-audio model devolved for research and demo purposes. It follows a GPT style architecture similar to [AudioLM](https://arxiv.org/abs/2209.03143) and [Vall-E](https://arxiv.org/abs/2301.02111) and a quantized Audio representation from [EnCodec](https://github.com/facebookresearch/encodec). It is not a conventional TTS model, but instead a fully generative text-to-audio model capable of deviating in unexpected ways from any given script. Different to previous approaches, the input text prompt is converted directly to audio without the intermediate use of phonemes. It can therefore generalize to arbitrary instructions beyond speech such as music lyrics, sound effects or other non-speech sounds. Below is a list of some known non-speech sounds, but we are finding more every day. Please let us know if you find patterns that work particularly well on [Discord](https://discord.gg/J2B2vsjKuE)! - `[laughter]` - `[laughs]` - `[sighs]` - `[music]` - `[gasps]` - `[clears throat]` - `โ€”` or `...` for hesitations - `โ™ช` for song lyrics - CAPITALIZATION for emphasis of a word - `[MAN]` and `[WOMAN]` to bias Bark toward male and female speakers, respectively ### Supported Languages | Language | Status | | --- | --- | | English (en) | โœ… | | German (de) | โœ… | | Spanish (es) | โœ… | | French (fr) | โœ… | | Hindi (hi) | โœ… | | Italian (it) | โœ… | | Japanese (ja) | โœ… | | Korean (ko) | โœ… | | Polish (pl) | โœ… | | Portuguese (pt) | โœ… | | Russian (ru) | โœ… | | Turkish (tr) | โœ… | | Chinese, simplified (zh) | โœ… | Requests for future language support [here](https://github.com/suno-ai/bark/discussions/111) or in the **#forums** channel on [Discord](https://discord.com/invite/J2B2vsjKuE). ## ๐Ÿ™ Appreciation - [nanoGPT](https://github.com/karpathy/nanoGPT) for a dead-simple and blazing fast implementation of GPT-style models - [EnCodec](https://github.com/facebookresearch/encodec) for a state-of-the-art implementation of a fantastic audio codec - [AudioLM](https://github.com/lucidrains/audiolm-pytorch) for related training and inference code - [Vall-E](https://arxiv.org/abs/2301.02111), [AudioLM](https://arxiv.org/abs/2209.03143) and many other ground-breaking papers that enabled the development of Bark ## ยฉ License Bark is licensed under the MIT License. Please contact us at `bark@suno.ai` to request access to a larger version of the model. ## ๐Ÿ“ฑย Community - [Twitter](https://twitter.com/OnusFM) - [Discord](https://discord.gg/J2B2vsjKuE) ## ๐ŸŽงย Suno Studio (Early Access) Weโ€™re developing a playground for our models, including Bark. If you are interested, you can sign up for early access [here](https://3os84zs17th.typeform.com/suno-studio). ## โ“ FAQ #### How do I specify where models are downloaded and cached? * Bark uses Hugging Face to download and store models. You can see find more info [here](https://huggingface.co/docs/huggingface_hub/package_reference/environment_variables#hfhome). #### Bark's generations sometimes differ from my prompts. What's happening? * Bark is a GPT-style model. As such, it may take some creative liberties in its generations, resulting in higher-variance model outputs than traditional text-to-speech approaches. #### What voices are supported by Bark? * Bark supports 100+ speaker presets across [supported languages](#supported-languages). You can browse the library of speaker presets [here](https://suno-ai.notion.site/8b8e8749ed514b0cbf3f699013548683?v=bc67cff786b04b50b3ceb756fd05f68c). The community also shares presets in [Discord](https://discord.gg/J2B2vsjKuE). Bark also supports generating unique random voices that fit the input text. Bark does not currently support custom voice cloning. #### Why is the output limited to ~13-14 seconds? * Bark is a GPT-style model, and its architecture/context window is optimized to output generations with roughly this length. #### How much VRAM do I need? * The full version of Bark requires around 12Gb of memory to hold everything on GPU at the same time. However, even smaller cards down to ~2Gb work with some additional settings. Simply add the following code snippet before your generation: ```python import os os.environ["SUNO_OFFLOAD_CPU"] = True os.environ["SUNO_USE_SMALL_MODELS"] = True ``` #### My generated audio sounds like a 1980s phone call. What's happening? * Bark generates audio from scratch. It is not meant to create only high-fidelity, studio-quality speech. Rather, outputs could be anything from perfect speech to multiple people arguing at a baseball game recorded with bad microphones.