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:
- 431c17bb6b57ec5301526abb1469c2b2f7c6d2417002c72baab31de04bbce7bc
- Size of remote file:
- 211 kB
- SHA256:
- 12a5ae62df1f7fec34c86ce8a46381d33704e761a32bbc167b00a1eace7f17c9
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