Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use mageec/whisper-tiny-hi-capstone with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mageec/whisper-tiny-hi-capstone with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mageec/whisper-tiny-hi-capstone")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mageec/whisper-tiny-hi-capstone") model = AutoModelForSpeechSeq2Seq.from_pretrained("mageec/whisper-tiny-hi-capstone") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8005e81840a0d37d451f811d65fdbee920a9cf2f417d5053eed720a93401b59d
- Size of remote file:
- 4.86 kB
- SHA256:
- f547006885aa84d7feafb7ec9a9132e77dcb9faf38c0b9d7e0b6e07df531065c
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