Instructions to use DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF",
	filename="L3.2-8X3B-GTD-MOE-NEO-Reason-Dark-Champ-uncen-18.4B-IMAT-D_AU-IQ2_M-imat.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF:Q4_K_M

Use Docker

docker model run hf.co/DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF:Q4_K_M

Ollama
How to use DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF with Ollama:
```
ollama run hf.co/DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF:Q4_K_M
```

Unsloth Studio

How to use DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF 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/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF 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/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF with Docker Model Runner:
```
docker model run hf.co/DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF:Q4_K_M
```

Lemonade

How to use DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull DavidAU/Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Llama-3.2-8X3B-GATED-MOE-NEO-Reasoning-Dark-Champion-uncensored-18.4B-IMAT-GGUF-Q4_K_M

List all available models

lemonade list

DavidAU commited on Jul 28, 2025

Commit

3885e93

verified ·

1 Parent(s): e7010e4

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	@@ -925,3 +925,42 @@ I'm excited to see where this story will take me, and I'm confident that I can c
925	[[[thinking end]]]
926
927

 [[[thinking end]]]
+---
+<h2>Special Thanks:</h2>
+---
+Special thanks to all the following, and many more...
+All the model makers, fine tuners, mergers, and tweakers:
+- Provides the raw "DNA" for almost all my models.
+- Sources of model(s) can be found on the repo pages, especially the "source" repos with link(s) to the model creator(s).
+Huggingface [ https://huggingface.co ] :
+- The place to store, merge, and tune models endlessly.
+- THE reason we have an open source community.
+LlamaCPP [ https://github.com/ggml-org/llama.cpp ] :
+- The ability to compress and run models on GPU(s), CPU(s) and almost all devices.
+- Imatrix, Quantization, and other tools to tune the quants and the models.
+- Llama-Server : A cli based direct interface to run GGUF models.
+- The only tool I use to quant models.
+Quant-Masters: Team Mradermacher, Bartowski, and many others:
+- Quant models day and night for us all to use.
+- They are the lifeblood of open source access.
+MergeKit [ https://github.com/arcee-ai/mergekit ] :
+- The universal online/offline tool to merge models together and forge something new.
+- Over 20 methods to almost instantly merge model, pull them apart and put them together again.
+- The tool I have used to create over 1500 models.
+Lmstudio [ https://lmstudio.ai/ ] :
+- The go to tool to test and run models in GGUF format.
+- The Tool I use to test/refine and evaluate new models.
+- LMStudio forum on discord; endless info and community for open source.
+Text Generation Webui // KolboldCPP // SillyTavern:
+- Excellent tools to run GGUF models with - [  https://github.com/oobabooga/text-generation-webui ] [ https://github.com/LostRuins/koboldcpp ] .
+- Sillytavern [ https://github.com/SillyTavern/SillyTavern ] can be used with LMSTudio [ https://lmstudio.ai/ ] , TextGen [ https://github.com/oobabooga/text-generation-webui ], Kolboldcpp [ https://github.com/LostRuins/koboldcpp ], Llama-Server [part of LLAMAcpp] as a off the scale front end control system and interface to work with models.