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-V2-Strong-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-V2-Strong-HERETIC-UNCENSORED-Thinking with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("DavidAU/gemma-4-E4B-it-The-DECKARD-V2-Strong-HERETIC-UNCENSORED-Thinking") model = AutoModelForMultimodalLM.from_pretrained("DavidAU/gemma-4-E4B-it-The-DECKARD-V2-Strong-HERETIC-UNCENSORED-Thinking", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use DavidAU/gemma-4-E4B-it-The-DECKARD-V2-Strong-HERETIC-UNCENSORED-Thinking with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for DavidAU/gemma-4-E4B-it-The-DECKARD-V2-Strong-HERETIC-UNCENSORED-Thinking to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for DavidAU/gemma-4-E4B-it-The-DECKARD-V2-Strong-HERETIC-UNCENSORED-Thinking to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for DavidAU/gemma-4-E4B-it-The-DECKARD-V2-Strong-HERETIC-UNCENSORED-Thinking to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="DavidAU/gemma-4-E4B-it-The-DECKARD-V2-Strong-HERETIC-UNCENSORED-Thinking", max_seq_length=2048, )
Update README.md
Browse files
README.md
CHANGED
|
@@ -36,6 +36,8 @@ tags:
|
|
| 36 |
- all use cases
|
| 37 |
---
|
| 38 |
|
|
|
|
|
|
|
| 39 |
<h2>gemma-4-E4B-it-The-DECKARD-V2-Strong-HERETIC-UNCENSORED-Thinking</h2>
|
| 40 |
|
| 41 |
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 STRONG/DEEPER tuning
|
|
|
|
| 36 |
- all use cases
|
| 37 |
---
|
| 38 |
|
| 39 |
+
<small>NOTE: Updated Jinja templates, Apr 14 2026 to improve performance.</small>
|
| 40 |
+
|
| 41 |
<h2>gemma-4-E4B-it-The-DECKARD-V2-Strong-HERETIC-UNCENSORED-Thinking</h2>
|
| 42 |
|
| 43 |
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 STRONG/DEEPER tuning
|