Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use DavidFM43/whisper-tiny-mind14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DavidFM43/whisper-tiny-mind14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DavidFM43/whisper-tiny-mind14")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("DavidFM43/whisper-tiny-mind14") model = AutoModelForSpeechSeq2Seq.from_pretrained("DavidFM43/whisper-tiny-mind14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 294d7558d0da9b9d9a5fcc0b14bada1f5b2d4cf359915153605c7cdd2066bbd9
- Size of remote file:
- 4.09 kB
- SHA256:
- 026213c167c4e0f12c5fed5f5183ad16c328d3a7e445a276a6762eb49fc1b141
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