Instructions to use charsiu/WavEmbed-ASR-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use charsiu/WavEmbed-ASR-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="charsiu/WavEmbed-ASR-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("charsiu/WavEmbed-ASR-roberta-base") model = AutoModelForSpeechSeq2Seq.from_pretrained("charsiu/WavEmbed-ASR-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b832cdb7b8c26faa671be09532d10266b792063c95d260b817858894fef76a6
- Size of remote file:
- 990 MB
- SHA256:
- ea6fa0eca42d393722a55178de7d33507869ea51f86e56f84fcda9afdf82eb8a
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