Instructions to use lukespeech/whisper-tiny-fo-temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukespeech/whisper-tiny-fo-temp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lukespeech/whisper-tiny-fo-temp")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("lukespeech/whisper-tiny-fo-temp") model = AutoModelForSpeechSeq2Seq.from_pretrained("lukespeech/whisper-tiny-fo-temp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d895c393aef6dfb170080861305d03bbe2d24b539d2e12b10f790e860b96c3e6
- Size of remote file:
- 151 MB
- SHA256:
- bc046e0f95a7e5313b106abb87a7aff66dc3acdf960fa2cba03bb70d308c08e4
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