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
- Xet hash:
- 9a4ae386a2ea4f42996bbbcacd6730ffa746e4abdbff1a30ce626fb02d7c52b6
- Size of remote file:
- 1.26 GB
- SHA256:
- fc8d4c4ee95928cadf655ad832c9367db981534e9efe9d4504def8d112ca482b
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