Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Oriya
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use Ranjit/odia_whisper_small_v3.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ranjit/odia_whisper_small_v3.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Ranjit/odia_whisper_small_v3.0")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Ranjit/odia_whisper_small_v3.0") model = AutoModelForSpeechSeq2Seq.from_pretrained("Ranjit/odia_whisper_small_v3.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 199 Bytes
3ce0659 | 1 2 3 4 5 6 7 8 | {
"epoch": 27.93,
"eval_loss": 0.2584499418735504,
"eval_runtime": 738.8296,
"eval_samples_per_second": 9.396,
"eval_steps_per_second": 0.294,
"eval_wer": 13.861446892066024
} |