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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- faa6e9db3afd2ce992ada569bc67c1df9674f2fc0766e3c14c4ba14f5fb1c992
- Size of remote file:
- 118 kB
- SHA256:
- c23f3a383bcc30f1f00658b1077a891543e419d7bddfe827f52140b7253d4364
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