Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabBeta/nb-whisper-small-semantic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabBeta/nb-whisper-small-semantic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-small-semantic")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-small-semantic") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabBeta/nb-whisper-small-semantic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Saving weights and logs of step 249 - epoch 0
9a03a34 -
Saving weights and logs of step 240 - epoch 0
8fe9d5f -
Saving weights and logs of step 200 - epoch 0
7c1fed3 -
Saving weights and logs of step 160 - epoch 0
2957d5c -
Saving weights and logs of step 120 - epoch 0
9a7ba49 -
Saving weights and logs of step 80 - epoch 0
67a14dc -
Saving weights and logs of step 40 - epoch 0
caf8ebf -
Saving weights and logs of step 0 - epoch 0
e1f749a