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:
- c898ff222431a12c459c31d9089684231a3332a7045199f43250b203c285c6b5
- Size of remote file:
- 3.06 GB
- SHA256:
- 45b31bfc73959046ae38493b77cddcb4545bb392657776d0cfb503dd4f8f30fb
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