Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Croatian
whisper
Generated from Trainer
Instructions to use 5roop/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 5roop/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="5roop/output")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("5roop/output") model = AutoModelForMultimodalLM.from_pretrained("5roop/output") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5aed01209bc314d5460b96046c394422ccf1c73899ecc56295d69a9feda470f6
- Size of remote file:
- 4.54 kB
- SHA256:
- 6c7c8afe35a9920337dea36688dd654ef483d047a5d808a5092c503e7f9e094e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.