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:
- d3f3a909637cbca25303d9f50d26593b7fbd07c4c22896dfbf937854e7ab6056
- Size of remote file:
- 3.06 GB
- SHA256:
- 30198a7d90649d9bb461cf9f024aa6aa0447d750e1b89dbfda33b98cec8a2fc3
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