Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use sjdata/whisper-tiny-minds14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sjdata/whisper-tiny-minds14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sjdata/whisper-tiny-minds14")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sjdata/whisper-tiny-minds14") model = AutoModelForSpeechSeq2Seq.from_pretrained("sjdata/whisper-tiny-minds14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a22bf159d85e583edb315f93729c6b5b002274b410ca17a8caffd0eee06812c3
- Size of remote file:
- 4.09 kB
- SHA256:
- 3d0353dff999db0351ff6b6534642e443008200236e07eda2fb0c8908e722172
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