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:
- 473131dfd450c698dbfb89977bf8e9be21262120c93918b1a942f2021814cd05
- Size of remote file:
- 4.97 GB
- SHA256:
- ac58e8ec7d74e14b05e5860b132b5424807f808e3b50807147c6a2031af744b0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.