Model reference · open weights
bark is an open-weight audio or speech model from suno, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
Bark Bark is a transformer-based text-to-audio model created by Suno. 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 ready for inference. The original github repo and model card can be found here. This model is meant for research purposes only. The model output is not censored and the authors do not endorse the opinions in the generated content. Use at your own risk. Two checkpoints are released: - small - large (this checkpoint) Example Try out Bark yourself! Bark Colab: Hugging Face Colab: Hugging Face Demo: 🤗 Transformers Usage You can run Bark locally with the 🤗 Transformers library from version 4.31.0 onwards. 1. First install the 🤗 Transformers library and scipy: 2. Run inference via the Text-to-Speech (TTS) pipeline. You can infer the bark model via the TTS pipeline in just a few lines of code! 3. Run inference via the Transformers modelling code. You can use the processor + generate code to convert text into a mono 24 kHz speech waveform for more fine-grained control. 4. Listen to the speech samples either in an ipynb notebook: Or save them as a .wav file using a third-party library, e.g. scipy: For more details on using the Bark model for inference using the 🤗 Transformers library, refer to the Bark docs. Suno Usage You can also run Bark locally through the original Bark library: 1. First install the bark library 2. Run the following Python code: pizza.webm To save audioarray as a WAV file: Model Details The following is additional information about the models released here. Bark is a series of three transformer models that turn text into audio. Text to semantic tokens - Input: text, tokenized with BERT tokenizer from Hugging Face - Output: semantic tokens that encode the audio to be generated Semantic to coarse tokens - Input: semantic tokens - Output: tokens from the first two codebooks of the EnCodec Codec from facebook Coarse to fine tokens - Input: the first two codebooks from EnCo
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | suno |
|---|---|
| Type | Audio & music |
| Variants | 1 |
| Runs with | transformers |
| Released | 2023-04-25 |
| Popularity | 38k downloads / month |
| Likes | 1,560 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| bark | — | BF16 | — | — | Weights ↗ |
Using it via the API
Once AxForge deploys bark for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (bark below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/audio/transcriptions \ -H "Authorization: Bearer $AXFORGE_API_KEY" \ -F model="bark" -F file=@audio.mp3
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Licence
Open weights under mit — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗