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, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("5roop/output") model = AutoModelForSpeechSeq2Seq.from_pretrained("5roop/output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1fdad067369570a64bc0778cc2f8e7fb5fa90c846f2b893755e57381571f3366
- Size of remote file:
- 5.39 kB
- SHA256:
- f4cbfe0e2c2adb65118808855e682ccb9428a33a9072fa0bad9e7673c588294f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.