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:
- 3bbff13b460537def85cfbd655d70f18fc04ad1142f057078f4d26fca6b3f63d
- Size of remote file:
- 4.99 GB
- SHA256:
- 4b42974ee6df2f903571235a7900cc909cd52ec5ac148fe5435d53b0d0d6be0b
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