Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use ahk-d/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahk-d/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ahk-d/whisper-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ahk-d/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("ahk-d/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b84967e871caac4c9b28fa38a244cb2f9713cbe1ad4e436f0056d8c174679ab
- Size of remote file:
- 5.43 kB
- SHA256:
- aaabe21cef8f75ed6cb055c1c68ded1f814b0b028ab284c34d52a45fd3424e45
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