Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
English
whisper
Generated from Trainer
Instructions to use LightFury9/whisper-tiny-ASR_mini_project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LightFury9/whisper-tiny-ASR_mini_project with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="LightFury9/whisper-tiny-ASR_mini_project")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("LightFury9/whisper-tiny-ASR_mini_project") model = AutoModelForSpeechSeq2Seq.from_pretrained("LightFury9/whisper-tiny-ASR_mini_project", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2c40f3de8afba4dce8c79bfe406482dad878871560056cef536f9ddb1966d0f
- Size of remote file:
- 4.73 kB
- SHA256:
- 713ec4e433894717288669474c0d354c46bd3f3fdc31aef09ea1f42ff5be86c1
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