Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Bengali
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use Redve/BengaliModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Redve/BengaliModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Redve/BengaliModel")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Redve/BengaliModel") model = AutoModelForSpeechSeq2Seq.from_pretrained("Redve/BengaliModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16ec27bff910c2f76ec3a1f3572b6ed01b522bc8eaeebd66902edb5eb78fd327
- Size of remote file:
- 4.86 kB
- SHA256:
- 054381633cf83dbfef6ff72f8d91414d0044eb480d426141915d5eb88bfa9fad
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