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:
- e6161f03c600b0e42a1922ecc55dd0aca7c001b3c3161bffa9b428941e72b9c1
- Size of remote file:
- 4.88 GB
- SHA256:
- f2f6781c0961b55fd8f58d5d339381028d993bc9a2a03bf882bd86d1b022b47d
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