Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Serbian
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Sagicc/whisper-large-v3-sr-combined with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sagicc/whisper-large-v3-sr-combined with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sagicc/whisper-large-v3-sr-combined")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Sagicc/whisper-large-v3-sr-combined") model = AutoModelForSpeechSeq2Seq.from_pretrained("Sagicc/whisper-large-v3-sr-combined") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
9d3a48d | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:9efb9cd7be014a599eede158a8dded763817dcab3b04cd3052980af7f6e3e3e3
size 4283
|