Instructions to use Subhadeep/whisper-base-bn-Dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Subhadeep/whisper-base-bn-Dev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Subhadeep/whisper-base-bn-Dev")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Subhadeep/whisper-base-bn-Dev") model = AutoModelForSpeechSeq2Seq.from_pretrained("Subhadeep/whisper-base-bn-Dev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
16ec022 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:3abb8bd7649ff6bd33f721c3b00dc3f9026e7e6cc67b1cf516c13afed772e97b
size 3643
|