Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Bulgarian
whisper
whisper-event
Generated from Trainer
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use shripadbhat/whisper-medium-bg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shripadbhat/whisper-medium-bg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="shripadbhat/whisper-medium-bg")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("shripadbhat/whisper-medium-bg") model = AutoModelForSpeechSeq2Seq.from_pretrained("shripadbhat/whisper-medium-bg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ff40331cae9f8a3c06b14fc74d774c11a74edbe3981f0cb0bb3988354321a3d
- Size of remote file:
- 3.06 GB
- SHA256:
- cb9dfcf9258acb641dfe20b83e4760eccce812f38690b8e30fbe2683d8dcb26b
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