Any-to-Any
Transformers
Safetensors
gemma4
image-text-to-text
heretic
uncensored
aliterated
finetune
unsloth
all use cases
coder
creative
creative writing
fiction writing
plot generation
sub-plot generation
story generation
scene continue
storytelling
fiction story
science fiction
romance
all genres
story
writing
vivid prosing
vivid writing
fiction
roleplaying
bfloat16
Instructions to use DavidAU/gemma-4-E4B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DavidAU/gemma-4-E4B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("DavidAU/gemma-4-E4B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking") model = AutoModelForMultimodalLM.from_pretrained("DavidAU/gemma-4-E4B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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<h2>gemma-4-E4B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking</h2>
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16 bit precision fine tune of Gemma 4 "E4B" (an 8B parameter model - see below) Heretic/Uncensored using "The Deckard" in house datasets [5] via Unsloth using light tuning
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<small>NOTE: Updated Jinja templates, Apr 14 2026 to improve performance.</small>
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<h2>gemma-4-E4B-it-The-DECKARD-HERETIC-UNCENSORED-Thinking</h2>
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16 bit precision fine tune of Gemma 4 "E4B" (an 8B parameter model - see below) Heretic/Uncensored using "The Deckard" in house datasets [5] via Unsloth using light tuning
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