Feature Extraction
Transformers
Safetensors
English
multilingual
gemma4_audio
audio
speech
conformer
gemma4
usm
google
Eval Results (legacy)
Instructions to use rnagabh/gemma4-audio-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rnagabh/gemma4-audio-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="rnagabh/gemma4-audio-encoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("rnagabh/gemma4-audio-encoder") model = AutoModel.from_pretrained("rnagabh/gemma4-audio-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Initial upload: Gemma 4 audio encoder (304.8M USM-style Conformer)
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Initial upload: Gemma 4 audio encoder (304.8M USM-style Conformer)
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Initial upload: Gemma 4 audio encoder (304.8M USM-style Conformer)
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Initial upload: Gemma 4 audio encoder (304.8M USM-style Conformer)
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Initial upload: Gemma 4 audio encoder (304.8M USM-style Conformer)
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Initial upload: Gemma 4 audio encoder (304.8M USM-style Conformer)
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Initial upload: Gemma 4 audio encoder (304.8M USM-style Conformer)
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Initial upload: Gemma 4 audio encoder (304.8M USM-style Conformer)
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Initial upload: Gemma 4 audio encoder (304.8M USM-style Conformer)
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initial commit
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