Instructions to use asafaya/hubert-large-arabic-transcribe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asafaya/hubert-large-arabic-transcribe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="asafaya/hubert-large-arabic-transcribe")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("asafaya/hubert-large-arabic-transcribe") model = AutoModel.from_pretrained("asafaya/hubert-large-arabic-transcribe", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update hyperparams.yaml
Browse files- hyperparams.yaml +1 -1
hyperparams.yaml
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@@ -45,7 +45,7 @@ enc: &id002 !new:speechbrain.nnet.containers.Sequential
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activation3: !new:torch.nn.GELU
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wav2vec2: !new:speechbrain.lobes.models.huggingface_wav2vec.HuggingFaceWav2Vec2
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source:
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output_norm: true
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freeze: false
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save_path: wav2vec2_checkpoint
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activation3: !new:torch.nn.GELU
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wav2vec2: !new:speechbrain.lobes.models.huggingface_wav2vec.HuggingFaceWav2Vec2
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source: asafaya/hubert-large-arabic-transcribe
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output_norm: true
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freeze: false
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save_path: wav2vec2_checkpoint
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