Instructions to use hf-internal-testing/tiny-random-MusicgenForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MusicgenForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="hf-internal-testing/tiny-random-MusicgenForConditionalGeneration")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-MusicgenForConditionalGeneration") model = AutoModelForTextToWaveform.from_pretrained("hf-internal-testing/tiny-random-MusicgenForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Upload ONNX weights (#40)
Verified signature- [Awaiting approval] Upload ONNX weights (b3b17bc07adce0d4961ec9ab33b89ba9c2d802bf) - Upload encodec_decode.onnx (c293eab66ad875363f5e8a2e0c892d3f647aa082)76fd55a
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Upload MusicgenForConditionalGeneration
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Upload tiny models for MusicgenForConditionalGeneration
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initial commit
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