Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
whisper
Generated from Trainer
whisper-event
Eval Results (legacy)
Instructions to use agnesluhtaru/whisper-small-et with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agnesluhtaru/whisper-small-et with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="agnesluhtaru/whisper-small-et")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("agnesluhtaru/whisper-small-et") model = AutoModelForSpeechSeq2Seq.from_pretrained("agnesluhtaru/whisper-small-et", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Training in progress, step 200
cd9c886
-
Training in progress, step 200
5aa9558 -
Training in progress, step 200
62ba3b3
-
Training in progress, step 1000
1a9e6f4
-
Training in progress, step 5000
0265a61 -
Training in progress, step 5000
cb0342f -
Training in progress, step 4000
eafeebe -
Training in progress, step 3000
91649d8 -
Training in progress, step 3000
a713132 -
Training in progress, step 2000
1261bc9 -
Training in progress, step 2000
6bf5b55
-
Training in progress, step 1000
2d7eda9 -
Training in progress, step 1000
9145382