Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Finnish
whisper
whisper-event
finnish
Eval Results (legacy)
Instructions to use Finnish-NLP/whisper-medium-finnish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Finnish-NLP/whisper-medium-finnish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Finnish-NLP/whisper-medium-finnish")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Finnish-NLP/whisper-medium-finnish") model = AutoModelForSpeechSeq2Seq.from_pretrained("Finnish-NLP/whisper-medium-finnish", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| language: | |
| - fi | |
| license: apache-2.0 | |
| tags: | |
| - whisper-event | |
| - finnish | |
| datasets: | |
| - mozilla-foundation/common_voice_11_0 | |
| - google/fleurs | |
| metrics: | |
| - wer | |
| - cer | |
| model-index: | |
| - name: Whisper Medium Finnish | |
| results: | |
| - task: | |
| name: Automatic Speech Recognition | |
| type: automatic-speech-recognition | |
| dataset: | |
| name: Common Voice 11.0 | |
| type: mozilla-foundation/common_voice_11_0 | |
| config: fi | |
| split: test | |
| args: fi | |
| metrics: | |
| - name: Wer | |
| type: wer | |
| value: 12.01 | |
| - name: Cer | |
| type: cer | |
| value: 2.27 | |
| - task: | |
| name: Automatic Speech Recognition | |
| type: automatic-speech-recognition | |
| dataset: | |
| name: FLEURS | |
| type: google/fleurs | |
| config: fi_fi | |
| split: test | |
| args: fi_fi | |
| metrics: | |
| - name: Wer | |
| type: wer | |
| value: 10.96 | |
| - name: Cer | |
| type: cer | |
| value: 2.99 | |