Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabBeta/nb-whisper-small-verbatim with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabBeta/nb-whisper-small-verbatim with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-small-verbatim")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-small-verbatim") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabBeta/nb-whisper-small-verbatim", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 170 Bytes
1d5d539 | 1 2 3 4 5 6 7 8 | {
"test": {
"cer": 2.5732242197469986,
"exact_cer": 2.591680985773774,
"exact_wer": 7.26509554369124,
"wer": 7.192589940934312
}
} |