Automatic Speech Recognition
Transformers
Safetensors
Finnish
wav2vec2
smi
sami
Eval Results (legacy)
Instructions to use GetmanY1/wav2vec2-large-sami-22k-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GetmanY1/wav2vec2-large-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-large-sami-22k-finetuned")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("GetmanY1/wav2vec2-large-sami-22k-finetuned") model = AutoModelForCTC.from_pretrained("GetmanY1/wav2vec2-large-sami-22k-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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library_name: transformers
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language: fi
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model-index:
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---
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# Sámi Wav2vec2-Large ASR
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library_name: transformers
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language: fi
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base_model:
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model-index:
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- name: wwav2vec2-large-sami-22k-finetuned
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Sami-1h-test
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type: sami-1h-test
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args: fi
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metrics:
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- name: Test WER
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type: wer
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value: 33.32
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- name: Test CER
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type: cer
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value: 12.76
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---
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# Sámi Wav2vec2-Large ASR
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