Instructions to use DazMashaly/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DazMashaly/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DazMashaly/output")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("DazMashaly/output") model = AutoModelForSpeechSeq2Seq.from_pretrained("DazMashaly/output") - Notebooks
- Google Colab
- Kaggle
Upload WhisperForConditionalGeneration
Browse files- config.json +1 -1
- model.safetensors +1 -1
config.json
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"_name_or_path": "
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"activation_dropout": 0.0,
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"activation_function": "gelu",
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"apply_spec_augment": false,
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"_name_or_path": "/kaggle/working/new_downloads/checkpoint-2863",
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"activation_dropout": 0.0,
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"activation_function": "gelu",
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"apply_spec_augment": false,
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model.safetensors
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