Instructions to use hf-internal-testing/tiny-random-unispeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-unispeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-unispeech")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-unispeech") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-unispeech") - Notebooks
- Google Colab
- Kaggle
Upload ONNX weights (#2)
Browse files- [Awaiting approval] Upload ONNX weights (8be843a7b9d460abbfd72504764530252d0e2921)
- onnx/model.onnx +3 -0
onnx/model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:95e7cd0f2e1e911e720d4cfd4bcb2e90630ff18f3b247d9a10ba70e20b2f8267
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size 244503
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