Instructions to use adepusricharan/echoforge-musicgen with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adepusricharan/echoforge-musicgen with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="adepusricharan/echoforge-musicgen")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("adepusricharan/echoforge-musicgen") model = AutoModelForTextToWaveform.from_pretrained("adepusricharan/echoforge-musicgen", device_map="auto") - Audiocraft
How to use adepusricharan/echoforge-musicgen with Audiocraft:
from audiocraft.models import MusicGen model = MusicGen.get_pretrained("adepusricharan/echoforge-musicgen") descriptions = ['happy rock', 'energetic EDM', 'sad jazz'] wav = model.generate(descriptions) # generates 3 samples. - Notebooks
- Google Colab
- Kaggle
File size: 275 Bytes
86c7117 | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"chunk_length_s": null,
"feature_extractor_type": "EncodecFeatureExtractor",
"feature_size": 2,
"overlap": null,
"padding_side": "left",
"padding_value": 0.0,
"processor_class": "MusicgenProcessor",
"return_attention_mask": true,
"sampling_rate": 32000
}
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