Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Kazakh
whisper
hf-asr-leaderboard
Generated from Trainer
Eval Results (legacy)
Instructions to use Drahokma/whisper-large-v3-kz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Drahokma/whisper-large-v3-kz with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Drahokma/whisper-large-v3-kz")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Drahokma/whisper-large-v3-kz") model = AutoModelForSpeechSeq2Seq.from_pretrained("Drahokma/whisper-large-v3-kz", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
README.md
CHANGED
|
@@ -7,7 +7,7 @@ tags:
|
|
| 7 |
- hf-asr-leaderboard
|
| 8 |
- generated_from_trainer
|
| 9 |
datasets:
|
| 10 |
-
- mozilla-foundation/
|
| 11 |
metrics:
|
| 12 |
- wer
|
| 13 |
model-index:
|
|
@@ -18,7 +18,7 @@ model-index:
|
|
| 18 |
type: automatic-speech-recognition
|
| 19 |
dataset:
|
| 20 |
name: Common Voice 17.0
|
| 21 |
-
type: mozilla-foundation/
|
| 22 |
config: kk
|
| 23 |
split: test
|
| 24 |
args: 'config: kk, split: test'
|
|
|
|
| 7 |
- hf-asr-leaderboard
|
| 8 |
- generated_from_trainer
|
| 9 |
datasets:
|
| 10 |
+
- mozilla-foundation/common_voice_17_0
|
| 11 |
metrics:
|
| 12 |
- wer
|
| 13 |
model-index:
|
|
|
|
| 18 |
type: automatic-speech-recognition
|
| 19 |
dataset:
|
| 20 |
name: Common Voice 17.0
|
| 21 |
+
type: mozilla-foundation/common_voice_17_0
|
| 22 |
config: kk
|
| 23 |
split: test
|
| 24 |
args: 'config: kk, split: test'
|