Any-to-Any
Transformers
Safetensors
gemma4_unified
image-text-to-text
heretic
uncensored
decensored
abliterated
reproducible
Instructions to use BinxNet/gemma-4-12B-it-heretic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BinxNet/gemma-4-12B-it-heretic with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("BinxNet/gemma-4-12B-it-heretic") model = AutoModelForMultimodalLM.from_pretrained("BinxNet/gemma-4-12B-it-heretic") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96a2ae8ab65bd4382605f2d056bbec894a921efe32524ea9221c4cb00182457b
- Size of remote file:
- 4.12 GB
- SHA256:
- d2bc72ec84ba843860759be33867faae7961e6502ba5c0992502548635ccbb88
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