Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Serbian
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Sagicc/whisper-small-sr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sagicc/whisper-small-sr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sagicc/whisper-small-sr")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Sagicc/whisper-small-sr") model = AutoModelForSpeechSeq2Seq.from_pretrained("Sagicc/whisper-small-sr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8dd7e4ea9427494c1935ae1365849901ac1dfc90749fdbdb7ff599daf1ecb7ba
- Size of remote file:
- 967 MB
- SHA256:
- 4a99d815c0c01a5ca5e486f4bc2122870c406073a32b70d0119854eaecf3679d
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