Automatic Speech Recognition
Transformers
Safetensors
Finnish
wav2vec2
smi
sami
Eval Results (legacy)
Instructions to use GetmanY1/wav2vec2-base-sami-22k-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GetmanY1/wav2vec2-base-sami-22k-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GetmanY1/wav2vec2-base-sami-22k-finetuned")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("GetmanY1/wav2vec2-base-sami-22k-finetuned") model = AutoModelForCTC.from_pretrained("GetmanY1/wav2vec2-base-sami-22k-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0a346222c7ab1a19f84c10a096b908afc90148a68116b1c4a6345f92dbfab3d7
- Size of remote file:
- 378 MB
- SHA256:
- bec92ea1d450bba4d658af4cfab72ec803af5943f51e645b2f0337a01f8f31db
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