Instructions to use malaysia-ai/gemma3n-audio-encoder-whisper-decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malaysia-ai/gemma3n-audio-encoder-whisper-decoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="malaysia-ai/gemma3n-audio-encoder-whisper-decoder", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("malaysia-ai/gemma3n-audio-encoder-whisper-decoder", trust_remote_code=True) model = AutoModel.from_pretrained("malaysia-ai/gemma3n-audio-encoder-whisper-decoder", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from malaysia-ai/gemma3n-audio-encoder-whisper-decoder: direct link, hf CLI and curl.
- Browser
- Download file 3.93 MB
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https://huggingface.co/malaysia-ai/gemma3n-audio-encoder-whisper-decoder/resolve/main/tokenizer.json
- Command line
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hf download hf://malaysia-ai/gemma3n-audio-encoder-whisper-decoder/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/malaysia-ai/gemma3n-audio-encoder-whisper-decoder/resolve/main/tokenizer.json
3.93 MB
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