Automatic Speech Recognition
Transformers
PyTorch
Armenian
Armenian
multilingual
wav2vec2
mozilla-foundation/common_voice_9_0
google/fleurs
Instructions to use YSU/aspram with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YSU/aspram with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="YSU/aspram")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("YSU/aspram") model = AutoModelForCTC.from_pretrained("YSU/aspram") - Notebooks
- Google Colab
- Kaggle
Add multilingual to the language tag
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by lbourdois - opened
README.md
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language:
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- hy
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- hye
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license: apache-2.0
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tags:
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- automatic-speech-recognition
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- hy
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- mozilla-foundation/common_voice_9_0
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- google/fleurs
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models:
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- facebook/wav2vec2-xls-r-2b
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datasets:
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- mozilla-foundation/common_voice_9_0
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- google/fleurs
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- mc4
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task_categories:
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- automatic-speech-recognition
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- speech-processing
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language:
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- hy
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- hye
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- multilingual
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license: apache-2.0
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tags:
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- automatic-speech-recognition
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- hy
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| 10 |
- mozilla-foundation/common_voice_9_0
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| 11 |
- google/fleurs
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datasets:
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- mozilla-foundation/common_voice_9_0
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- google/fleurs
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- mc4
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models:
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- facebook/wav2vec2-xls-r-2b
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task_categories:
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- automatic-speech-recognition
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- speech-processing
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