Any-to-Any
Transformers
Safetensors
gemma4
image-text-to-text
heretic
uncensored
decensored
abliterated
reproducible
Instructions to use BinxNet/gemma-4-E4B-it-heretic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BinxNet/gemma-4-E4B-it-heretic with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("BinxNet/gemma-4-E4B-it-heretic") model = AutoModelForMultimodalLM.from_pretrained("BinxNet/gemma-4-E4B-it-heretic") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1801ce70cf4a0738a2a9c1ebb9e9907520520c1acdf561973221324a1ed3d5ff
- Size of remote file:
- 5 GB
- SHA256:
- 21916333d2010bfe7e4b256c31971e6814f7565808093a774bf29358aa4cb3db
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