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:
- 2339c13122c893752d12434c4c83631d77e23b53fc692ea0b5abceea2f1d9d73
- Size of remote file:
- 4.99 GB
- SHA256:
- 6c287a613f4db9b189488a8429d73fbe8ae9a6f77e297d58836548abb86e1ffe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.