Instructions to use hf-internal-testing/tiny-random-Wav2Vec2Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Wav2Vec2Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-Wav2Vec2Model")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2Model") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3b449c2c89d72a964336a3420a9924026a043c2bf2703ebefdbf945f9e53391c
- Size of remote file:
- 132 kB
- SHA256:
- 75488894fe8b73be48144a0e7a2e79349b8335eee1d29db4d3a198de45795b73
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