Instructions to use hf-internal-testing/tiny-random-MimiModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MimiModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MimiModel")# Load model directly from transformers import AutoFeatureExtractor, AutoModel extractor = AutoFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-MimiModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MimiModel") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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dummy_decoder_inputs = torch.randint(8, (4,
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torch.onnx.export(
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decoder,
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dummy_decoder_inputs,
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dummy_decoder_inputs = torch.randint(8, (4, model.config.num_quantizers, 91))
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torch.onnx.export(
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decoder,
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dummy_decoder_inputs,
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