Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabBeta/nb-whisper-tiny-semantic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabBeta/nb-whisper-tiny-semantic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-tiny-semantic")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-tiny-semantic") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabBeta/nb-whisper-tiny-semantic") - Notebooks
- Google Colab
- Kaggle
Saving test results
Browse files
runs/Dec08_21-35-59_t1v-n-28421bce-w-4/events.out.tfevents.1702071359.t1v-n-28421bce-w-4.137032.0.v2
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c700b2a653f00ab69ca7f550786fcf9c05794929746f37cece67cbc0d13159fe
|
| 3 |
+
size 1524998
|
test_results.json
ADDED
|
@@ -0,0 +1,14 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"test_clean_stortinget_no": {
|
| 3 |
+
"cer": 10.549717723657642,
|
| 4 |
+
"exact_cer": 11.355945924067028,
|
| 5 |
+
"exact_wer": 22.608060392061365,
|
| 6 |
+
"wer": 18.28808904658906
|
| 7 |
+
},
|
| 8 |
+
"test_nst": {
|
| 9 |
+
"cer": 3.1179276161975125,
|
| 10 |
+
"exact_cer": 3.2606798747164127,
|
| 11 |
+
"exact_wer": 9.843143684757063,
|
| 12 |
+
"wer": 8.924960376017927
|
| 13 |
+
}
|
| 14 |
+
}
|