Colab Notebooks: These need updating, but they should work soon if they have a problem at the moment.
Scroll down to Bark AMD (DirectML) MANUAL Install
- Just the regular Windows NVIDIA drivers.
- You don't need anything else installed.
- You don't need Python.
- You don't need Pytorch.
- You don't need anything with
CUDAin the name. - In fact, other Python/CUDA things on your system could cause problems, if those were not installed in isolated environment like a conda or venv.
- To check, you can try going to a command line and typing
python --versionorpip listand seeing what shows up. Ideally you want those commands to do nothing because that means nothing is installed on your base windows system itself.
- (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. (Color text is coming back so you will want this later.)
- Download the latest zip file from the releases page: https://github.com/JonathanFly/bark-installer/releases
- Extract the zip file into a directory with no spaces in the filename. This is the folder where Bark will be installed.
- Click on
INSTALL_BARK_INFINITY.bat(you do not need to be administrator) - If the install finished with no errors, close that terminal window. Close any other open command line windows as well.
- Click
START_BARK_INFINITY.batfor the GUI version, orCOMMAND_LINE_BARK_INFINITY.batfor the command line version.
- Windows permissions error: Check for antivirus or security settings that may be blocking the installer. Can also be random and retrying the installer again simply fixes it.
- CondaSSLError, SSL Certificate Error: This is an odd one. If your country or government has an online ID card, you may have to uninstall the government SSL certificates.
- Try
TROUBLESHOOT_BARK_INFINITY.batfor some options. - Still Not Working? Feel free to @ me on Bark Official Discord, username "Jonathan Fly" jonathanfly.
- Delete the entire directory where you installed Bark.
โ ๏ธ Any Bark samples you made will be in that bark folder, so be sure to save anything you want before deleting the bark folder.
- Delete the Bark models. The Bark models will be in your Huggingface Cache directory. The location should be printed when you run Bark in the console as
Bark Model Location:orHF_HOME(for some older installs). The default location isC:\Users\YourWindowsUserName\.cache\in Windows. (You can generally delete anything in there and it will redownload if needed.)
- Search the Bark Discord for voices. The Bark Discord is abuzz with Suno's new music 'Chirp' model, but you can find many great voices posted in chat in the months since Bark was released.
- Bark Speaker Directory from rsxdalv: https://github.com/rsxdalv/bark-speaker-directory
- You can nag me in Discord and if I'm online I might have some handy.
- Wait: I keep meaning to organize a bunch of good voices and update this repo.
I added an extremely basic way to do this over here but might still be useful. All this does it basically remove non-speech text from the .srt file so you can use it as a regular prompt. It doesn't add the new audio into a new video file or generate new subtitles, etc. Just inputs.
- Copy .SRT text file content and paste it into text prompt field.
- Run SRT text transformations in order. 1,2,3 etc. You can decide whether or not to leave the [action] text in, sometimes things like [grunts] work in Bark, depending on the voice.
- Decide how you want to split the text:
Render an audio segment for each original subtitle: After step two, your text input field should have the dialog in each subtitle on its own line in the text prompt. To render each line as segment, choose "advanced text splitting" and "Option 1" in the image. Process chunks of: "line", group by "line", start new clip when: "1". Because some subtitles have no dialog the number of segments may not line up be the same as the original subtitle file. If you want it to match you may want to skip step 5.
Render audio segments for the content, generally: Split the text normally how you would in Bark. This just ignores lines and counts by sentences, words, etc. For example "Option 2" is a common split: process chunks of: "sentence", group by: "word", start new clip when: "20". That will split by sentences and add new sentences until total words is over 20, then start a new segment.
- Tradeoff A Little Quality: Use just the small coarse Bark model, leave other two models (text and fine) regular sized. You can do this in the Gradio UI or the command line with an option.
- Try the new Huggingface Bark Implementation and see https://huggingface.co/blog/optimizing-bark with optimization suggestions.
- Try Pytorch nightly, if you know your way around the installation.
- Try optimizing numpy and other related libraries CPU libraries, because bark may be bottlenecked somewhat on CPU. For example Intel MKL may be worth a shot so you could try something like this:
- Linux (or WSL) seems generally a little faster than Windows, but I'm not sure if this is always true.
This is not part of the installer because it can break things, here for people who comfortable tweaking and rebuilding their Python conda environments.
- Type
COMMAND_LINE_BARK_INFINITY.bat - Type
python bark_perform.py --run_numpy_benchmark True - Note the benchmark times.
- Install MKL exe in Windows itself. https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl-download.html
- Install MKL in Python. Theres's a few different ways to install, one way you can try:
- Run
COMMAND_LINE_BARK_INFINITY.bat - Type:
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
- Run
- Rerun steps 1 and 2. Is it faster? If so, some chance Bark may be too.
- On apple, try setting
SUNO_ENABLE_MPSTrue - Watch this repo: https://github.com/PABannier/bark.cpp
- New: Intel BigDL just added Bark: intel-analytics/ipex-llm#9016
Sometimes I post at twitter.com/jonathanfly
An expensive AMD card will be a lot faster than using CPU, but a lot slower than a much less-expensive NVIDIA GPU like a 3060. If you really know your way around linux some people have reportedly compiled custom ROCm pytorch and say they got Bark working on AMD pretty decently - but there's no guide that I know of. This AMD install uses DirectML instead of of ROCm, easier but slower.
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.
You always want to see (pydyml_torch2) in the corner when installing and using Bark. If you don't see it from this point, you are in the wrong conda environment and need to type conda activate pydml_torch2 again.
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.
pip install torch==2.0.0 torchvision==0.15.1 torch-directml==0.2.0.dev230426 opencv-python torchvision==0.15.1 wget 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
Note: (you may be able to skip git checkout bark_amd_directml_test and use main branch, if not, you will be able to soon)
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:
- Voice Cloning (might work?)
- Top_k and top_p
- Probably more things I haven't tested.
- Click Anaconda Prompt in start menu
conda activate pydml_torch2- cd bark
python bark_webui.py
โ ๏ธ โฌ๏ธโฌ๏ธ Everything below this point is out of date - may have some useful info. โฌ๏ธโฌ๏ธ โ ๏ธ
(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)
-
Go here: https://github.com/conda-forge/miniforge#mambaforge
-
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.
-
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.
-
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)".
- 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.)
- 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 LINES START HERE (Also MacOS)
mamba install -y -k ninja git
pip install torch torchvision torchaudio
##### CPU ONLY LINES END HERE (Also 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
python bark_perform.py
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.)
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
git pull
pip install -r barki-allpip.txt --upgrade
Bark Infinity started as a humble ๐ป command line wrapper, a CLI ๐ฌ. Built from simple keyword commands, it was a proof of concept ๐งช, a glimmer of potential ๐ก.
Bark Infinity evolved ๐งฌ, expanding across dimensions ๐. Infinite Length ๐ต๐, Infinite Voices ๐๐, and a true high point in human history: ๐ Infinite Awkwardness ๐บ. But for some people, the time-tested command line interface was not a good fit. Many couldn't even try Bark ๐, struggling with CUDA gods ๐ฉ and being left with cryptic error messages ๐ง and a chaotic computer ๐พ. Many people felt veryโฆ UN INFINITE.
๐ (Non emoji real answer: A node based UI like ComfyUI, if Gradio 4.0 makes Audio a lot better.)
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.
๐ 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.)
whoami.mp4
Any length prompt and audio clips. Sometimes the final result is seamless, sometimes it's stable (but usually not both!).
๐ต 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?
but_are_we_strangers_to_love_really.mp4
Confused Travolta 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.
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.
almost_a_real_joke.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.)
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