Instructions to use avasaz/avasaz-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use avasaz/avasaz-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="avasaz/avasaz-large")# Load model directly from transformers import AutoTokenizer, AutoModelForTextToWaveform tokenizer = AutoTokenizer.from_pretrained("avasaz/avasaz-large") model = AutoModelForTextToWaveform.from_pretrained("avasaz/avasaz-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- efc7935c5c8bab65d41cae48b323691e2484b48c8d2ed45a65911b842e996a23
- Size of remote file:
- 6.51 GB
- SHA256:
- 1f0cf17b5e65c5dd8ba71767371c377f174e4ce1db44bc4d6657825769f26ffd
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