Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use JackismyShephard/whisper-tiny-finetuned-minds14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JackismyShephard/whisper-tiny-finetuned-minds14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="JackismyShephard/whisper-tiny-finetuned-minds14")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("JackismyShephard/whisper-tiny-finetuned-minds14") model = AutoModelForSpeechSeq2Seq.from_pretrained("JackismyShephard/whisper-tiny-finetuned-minds14") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93fdc53a58bbbe6c164cde7703f11fe6fe1c01efeb8f39829a80185b9144c9d6
- Size of remote file:
- 4.92 kB
- SHA256:
- 542d92d7296d31528aac951982c8d62414064e40c94904ffb34156a3563a0242
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.