Instructions to use wejoncy/gemma-4-E4B-fp8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wejoncy/gemma-4-E4B-fp8 with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("wejoncy/gemma-4-E4B-fp8") model = AutoModelForMultimodalLM.from_pretrained("wejoncy/gemma-4-E4B-fp8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19776cbbc7aee364a619ad299d75b3e5cc60fc3b32c9f94db19cca950b9d967d
- Size of remote file:
- 32.2 MB
- SHA256:
- 1f093437049fdbd2d08380bf67c207ebeccf02fc5dc43804b32c3968434a7d08
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