Instructions to use diarray/bam-vits with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use diarray/bam-vits with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="diarray/bam-vits")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("diarray/bam-vits") model = AutoModelForMultimodalLM.from_pretrained("diarray/bam-vits") - Notebooks
- Google Colab
- Kaggle
| { | |
| "feature_extractor_type": "VitsFeatureExtractor", | |
| "feature_size": 80, | |
| "hop_length": 256, | |
| "max_wav_value": 32768.0, | |
| "n_fft": 1024, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": false, | |
| "sampling_rate": 22050 | |
| } | |