Instructions to use suno/bark-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use suno/bark-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="suno/bark-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("suno/bark-small") model = AutoModelForTextToWaveform.from_pretrained("suno/bark-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from suno/bark-small: direct link, hf CLI and curl.
- Browser
- Download file 353 Bytes
-
https://huggingface.co/suno/bark-small/resolve/refs%2Fpr%2F13/tokenizer_config.json
- Command line
-
hf download hf://suno/bark-small@refs/pr/13/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/suno/bark-small/resolve/refs%2Fpr%2F13/tokenizer_config.json
353 Bytes
| { | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "[CLS]", | |
| "do_lower_case": false, | |
| "mask_token": "[MASK]", | |
| "model_max_length": 512, | |
| "pad_token": "[PAD]", | |
| "processor_class": "BarkProcessor", | |
| "sep_token": "[SEP]", | |
| "strip_accents": null, | |
| "tokenize_chinese_chars": true, | |
| "tokenizer_class": "BertTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |