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:
- b623f41a7a2fe9ae19771e99bc10da430e82d6db50e5d58b7332ea21f8614ef9
- Size of remote file:
- 3.06 GB
- SHA256:
- e593d9d109dea4a7d0d580ba19b8a9d734f48eaff804eea71d0412955d48a73f
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