Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Bengali
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Shamik/whisper-small-bn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shamik/whisper-small-bn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Shamik/whisper-small-bn")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Shamik/whisper-small-bn") model = AutoModelForSpeechSeq2Seq.from_pretrained("Shamik/whisper-small-bn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74fcde94a1b0d4f30aa87717d6b46bc662f8ca976eda3f095932c9ed2631f2e2
- Size of remote file:
- 4.41 kB
- SHA256:
- b5d761f8ab257b3d464b8e2cee098f86006b5572870f0ad2ef533f928b8403be
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