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:
- 525404495352cd04082c3ffc8da21e4700c7a5c7fb8f40efb9532beb9b20f299
- Size of remote file:
- 3.98 GB
- SHA256:
- f465c658b507cea4fc6231af7acdae9c7ed729e47c0ea63f88309f0202803ec4
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