Automatic Speech Recognition
Transformers
PyTorch
Basque
wav2vec2
mozilla-foundation/common_voice_8_0
Generated from Trainer
robust-speech-event
et
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use shpotes/xls-r-eus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shpotes/xls-r-eus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="shpotes/xls-r-eus")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("shpotes/xls-r-eus") model = AutoModelForCTC.from_pretrained("shpotes/xls-r-eus", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload README.md
Browse files
README.md
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- generated_from_trainer
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- robust-speech-event
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- et
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datasets:
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- mozilla-foundation/common_voice_8_0
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model-index:
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- name:
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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: Common Voice 8
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type: mozilla-foundation/common_voice_8_0
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args: eu
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metrics:
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- generated_from_trainer
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- robust-speech-event
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- et
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- hf-asr-leaderboard
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datasets:
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- mozilla-foundation/common_voice_8_0
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model-index:
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- name: xls-r-eus
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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: Common Voice 8
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type: mozilla-foundation/common_voice_8_0
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args: eu
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metrics:
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- name: Test WER
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type: wer
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value: 0.17871523648578164
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- name: Test CER
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type: cer
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value: 0.032624506085144
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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