Instructions to use malinoori/wav2vec2-base-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malinoori/wav2vec2-base-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="malinoori/wav2vec2-base-2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("malinoori/wav2vec2-base-2") model = AutoModelForCTC.from_pretrained("malinoori/wav2vec2-base-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5a72c9fffdaea917ccba7291fa50ae9f1ed6f3415c4225cf64b20ffa46b0aaf
- Size of remote file:
- 2.99 kB
- SHA256:
- 005e00a1cf5234db0580f6d79b19c0944744f03840a82a33f0bb055b7eb3cdeb
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