Automatic Speech Recognition
Transformers
PyTorch
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use steja/whisper-large-shona with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use steja/whisper-large-shona with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="steja/whisper-large-shona")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("steja/whisper-large-shona") model = AutoModelForSpeechSeq2Seq.from_pretrained("steja/whisper-large-shona", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3a557a5411096e5e6dd9190d77787f9bf60e234eee0ecb84d5bd583a9ad19418
- Size of remote file:
- 4.67 kB
- SHA256:
- 0d996b847634ae48932d879d37157d549f850ad46291d2c119cc1c52412cc681
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