Instructions to use seastar105/whisper-small-komixv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seastar105/whisper-small-komixv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="seastar105/whisper-small-komixv2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("seastar105/whisper-small-komixv2") model = AutoModelForSpeechSeq2Seq.from_pretrained("seastar105/whisper-small-komixv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1f10ebf39381a3a7113ecd9fabe7ce35cbe3eb0b5efc8ec183aef7ad1d88b84
- Size of remote file:
- 967 MB
- SHA256:
- 370b648897cd6800d43f76c03d9db8acebd9cd8cc6347ff26905e432800c0400
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