Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Northern Sami
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use NbAiLab/whisper-large-sme with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/whisper-large-sme with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/whisper-large-sme")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/whisper-large-sme") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/whisper-large-sme", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 1.0, | |
| "eval_loss": 0.5558891892433167, | |
| "eval_runtime": 163.4842, | |
| "eval_samples_per_second": 0.612, | |
| "eval_steps_per_second": 0.104, | |
| "eval_wer": 24.914285714285715, | |
| "train_loss": 3.482638488374606e-09, | |
| "train_runtime": 45.4914, | |
| "train_samples_per_second": 15827.168, | |
| "train_steps_per_second": 1318.931 | |
| } |