Instructions to use blackhole33/whisper-aisha-uz.v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use blackhole33/whisper-aisha-uz.v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="blackhole33/whisper-aisha-uz.v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("blackhole33/whisper-aisha-uz.v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("blackhole33/whisper-aisha-uz.v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e8dcfa481905e0170471d3764f566945cd77e5d8c05352f88ea51d28601b512
- Size of remote file:
- 4.22 kB
- SHA256:
- a3b9508a213e6bb65f511657525698704b2cb8164d305aee3eb6df535910e033
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