Instructions to use hf-internal-testing/tiny-random-Wav2Vec2ForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Wav2Vec2ForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-Wav2Vec2ForMaskedLM")# Load model directly from transformers import AutoProcessor, AutoModelForMaskedLM processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c2da8297fc429b86cba08ac9edf0bd7b3335e93139b23517edf9d9e48f518a7
- Size of remote file:
- 135 kB
- SHA256:
- a5f43e0c1ae230b68be95711215fe504667be67f53afa8739b6a9ffc4d5ec113
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