Instructions to use D4ve-R/wav2vec2-large-xlsr-53-german with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use D4ve-R/wav2vec2-large-xlsr-53-german with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="D4ve-R/wav2vec2-large-xlsr-53-german")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("D4ve-R/wav2vec2-large-xlsr-53-german") model = AutoModelForCTC.from_pretrained("D4ve-R/wav2vec2-large-xlsr-53-german", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31f328cbf595d9a489ffbd55a125deaa85739f6b06507e9e5813a79e22263e80
- Size of remote file:
- 1.26 GB
- SHA256:
- b37481845edac044ba3432f6c44919b1af32c092d503adfecc0d704dc458b6d5
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