Instructions to use BinaryLight1011/Musicbeat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BinaryLight1011/Musicbeat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="BinaryLight1011/Musicbeat")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BinaryLight1011/Musicbeat", device_map="auto") - PEFT
How to use BinaryLight1011/Musicbeat with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
| { | |
| "feature_extractor": { | |
| "chunk_length_s": null, | |
| "feature_extractor_type": "EncodecFeatureExtractor", | |
| "feature_size": 1, | |
| "overlap": null, | |
| "padding_side": "left", | |
| "padding_value": 0.0, | |
| "return_attention_mask": true, | |
| "sampling_rate": 32000 | |
| }, | |
| "processor_class": "MusicgenProcessor" | |
| } | |