Any-to-Any
Transformers
Safetensors
gemma4
image-text-to-text
obliteratus
abliterated
uncensored
multimodal
bfloat16
refusal-reduction
Instructions to use KridgeDookie/Gemma-4-E4B-IT-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KridgeDookie/Gemma-4-E4B-IT-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("KridgeDookie/Gemma-4-E4B-IT-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS") model = AutoModelForMultimodalLM.from_pretrained("KridgeDookie/Gemma-4-E4B-IT-ABLITERATED-UNCENSORED-PHILADELPHIA-CLASS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd2e82368c71fd60deb60d75d6d72701e0e6d1db2b22144f30c73cf3ac9c8781
- Size of remote file:
- 32.2 MB
- SHA256:
- 0d1d10b5165f3543ad0acbe0ad21105552c7a179fbb90a0d4b73ea22513f954a
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