Instructions to use ylacombe/bark-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ylacombe/bark-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="ylacombe/bark-large")# Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("ylacombe/bark-large") model = AutoModelForTextToWaveform.from_pretrained("ylacombe/bark-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update tokenizer_config.json
Browse files- tokenizer_config.json +1 -0
tokenizer_config.json
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]",
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"return_tensors": "pt",
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"max_length": 256,
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"tokenizer_type": "bert",
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"unk_token": "[UNK]",
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"return_tensors": "pt",
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"max_length": 256,
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