Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLab/nb-whisper-small-beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/nb-whisper-small-beta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/nb-whisper-small-beta")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/nb-whisper-small-beta") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/nb-whisper-small-beta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -19,21 +19,6 @@ metrics:
|
|
| 19 |
- cer
|
| 20 |
library_name: transformers
|
| 21 |
pipeline_tag: automatic-speech-recognition
|
| 22 |
-
inference:
|
| 23 |
-
parameters:
|
| 24 |
-
language: "no"
|
| 25 |
-
generate_kwargs:
|
| 26 |
-
language: "no"
|
| 27 |
-
forced_decoder_ids:
|
| 28 |
-
-
|
| 29 |
-
- 1
|
| 30 |
-
- 50288
|
| 31 |
-
-
|
| 32 |
-
- 2
|
| 33 |
-
- 50359
|
| 34 |
-
-
|
| 35 |
-
- 3
|
| 36 |
-
- 50363
|
| 37 |
widget:
|
| 38 |
- src: https://datasets-server.huggingface.co/assets/google/fleurs/--/nb_no/train/1/audio/audio.mp3
|
| 39 |
example_title: FLEURS sample 1
|
|
|
|
| 19 |
- cer
|
| 20 |
library_name: transformers
|
| 21 |
pipeline_tag: automatic-speech-recognition
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 22 |
widget:
|
| 23 |
- src: https://datasets-server.huggingface.co/assets/google/fleurs/--/nb_no/train/1/audio/audio.mp3
|
| 24 |
example_title: FLEURS sample 1
|