🛠️ Hardware and Inference Speedīark has been tested and works on both CPU and GPU ( pytorch 2.0+, CUDA 11.7 and CUDA 12.0). 💾 You can now use Bark with GPUs that have low VRAM (<4GB).Ĭd bark & pip install. 💬 Growing community support and access to new features here: We hope this resource helps you find useful prompts for your use cases! You can also join us on Discord, where the community actively shares useful prompts in the #audio-prompts channel. 📕 Long-form generation, voice consistency enhancements and other examples are now documented in a new notebooks section. We also added an option for a smaller version of Bark, which offers additional speed-up with the trade-off of slightly lower quality. ©️ Bark is now licensed under the MIT License, meaning it's now available for commercial use! Use at your own risk, and please act responsibly. Suno does not take responsibility for any output generated. 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. ⚠ Disclaimerīark was developed for research purposes. To support the research community, we are providing access to pretrained model checkpoints, which are ready for inference and available for commercial use. The model can also produce nonverbal communications like laughing, sighing and crying. Bark can generate highly realistic, multilingual speech as well as other audio - including music, background noise and simple sound effects.
Bark is a transformer-based text-to-audio model created by Suno.
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