Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Kazakh
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use Drahokma/whisper-large-v3-kz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Drahokma/whisper-large-v3-kz with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Drahokma/whisper-large-v3-kz")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Drahokma/whisper-large-v3-kz") model = AutoModelForSpeechSeq2Seq.from_pretrained("Drahokma/whisper-large-v3-kz", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9af58bf0ef7509786c1d83aa200d56aa0f4ff643f630f67c06056628ce78cf3d
- Size of remote file:
- 1.18 GB
- SHA256:
- 8c48dc3ae9e1f0d59e20d6d3beb74afa3b0947cf45c47641c72c6083c52b67e2
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