Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use innovation64/whisper-tiny-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use innovation64/whisper-tiny-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="innovation64/whisper-tiny-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("innovation64/whisper-tiny-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("innovation64/whisper-tiny-dv") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f632ee81f182e906e5cd8aa2bc69a93b2cc042095618723267f5eb3bb0c804f
- Size of remote file:
- 4.66 kB
- SHA256:
- 640978eff5d7fbcf18980684727610de76f94a0d060902a05a57d6eac17b7a91
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