Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Kabyle
wav2vec2
mozilla-foundation/common_voice_8_0
Generated from Trainer
sw
robust-speech-event
model_for_talk
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use Akashpb13/Kabyle_xlsr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akashpb13/Kabyle_xlsr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Akashpb13/Kabyle_xlsr")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Akashpb13/Kabyle_xlsr") model = AutoModelForCTC.from_pretrained("Akashpb13/Kabyle_xlsr") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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by librarian-bot - opened
README.md
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@@ -12,23 +12,24 @@ tags:
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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: Akashpb13/Kabyle_xlsr
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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: kab
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metrics:
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type: wer
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value: 0.3188425282720088
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-
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value: 0.09443079928558358
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---
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# Akashpb13/Kabyle_xlsr
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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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base_model: facebook/wav2vec2-xls-r-300m
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model-index:
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- name: Akashpb13/Kabyle_xlsr
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results:
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- task:
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type: automatic-speech-recognition
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name: 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: kab
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metrics:
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- type: wer
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value: 0.3188425282720088
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name: Test WER
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- type: cer
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value: 0.09443079928558358
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name: Test CER
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---
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# Akashpb13/Kabyle_xlsr
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