Instructions to use seastar105/whisper-medium-komixv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seastar105/whisper-medium-komixv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="seastar105/whisper-medium-komixv2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("seastar105/whisper-medium-komixv2") model = AutoModelForSpeechSeq2Seq.from_pretrained("seastar105/whisper-medium-komixv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5a21556e0eba37c39195775f54b1b518e409d1da054357f2b82e4621979eaa1
- Size of remote file:
- 3.06 GB
- SHA256:
- 11d24c92fe7b8200d3f2f8457a152aacdbb8a2456a1791cd1ff3a167106a4191
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