Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Slovenian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use shripadbhat/whisper-medium-sl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shripadbhat/whisper-medium-sl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="shripadbhat/whisper-medium-sl")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("shripadbhat/whisper-medium-sl") model = AutoModelForSpeechSeq2Seq.from_pretrained("shripadbhat/whisper-medium-sl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 41d8f0acf1cf25900467041ee244f79bc3b68396452a44063182ecc8127acdda
- Size of remote file:
- 3.64 kB
- SHA256:
- f1f183cc133ef53ffd92b095b71c355bbd0fbaacf694ce3c05a4d552c96b00c1
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