Instructions to use DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-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/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-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/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf:Q4_K_M

Use Docker

docker model run hf.co/DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf:Q4_K_M

LM Studio
Jan

vLLM

How to use DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf:Q4_K_M

Ollama
How to use DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf with Ollama:
```
ollama run hf.co/DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf:Q4_K_M
```

Unsloth Studio

How to use DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-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/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-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/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-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/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf to start chatting

Docker Model Runner
How to use DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf with Docker Model Runner:
```
docker model run hf.co/DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf:Q4_K_M
```

Lemonade

How to use DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull DavidAU/Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf:Q4_K_M

Run and chat with the model

lemonade run user.Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf-Q4_K_M

List all available models

lemonade list

Atomic Chat

DavidAU commited on Mar 5, 2025

Commit

07b1e6d

verified ·

1 Parent(s): c2aca93

Update README.md

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README.md CHANGED Viewed

@@ -29,7 +29,7 @@ tags:
 pipeline_tag: text-generation
 ---
-(quants uploading, examples to be added)
 <H2>Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf</H2>
@@ -86,6 +86,8 @@ Four examples below so you have some idea what this model can do.
 Keep in mind this model is two 1.5B parameters models working together, and will not have the power of a 14B or 32B reasoning/thinking model.
 Temp of .4 to .8 is suggested (for best reasoning/thinking), however it will still operate at much higher temps like 1.8, 2.6 etc.
 Depending on your prompt change temp SLOWLY: IE: .41,.42,.43 ... etc etc.

 pipeline_tag: text-generation
 ---
+(quants uploading, 5 examples below)
 <H2>Qwen2.5-MOE-2X1.5B-DeepSeek-Uncensored-Censored-4B-gguf</H2>
 Keep in mind this model is two 1.5B parameters models working together, and will not have the power of a 14B or 32B reasoning/thinking model.
+However, sometimes it will generate truly "out of the park" responses.
 Temp of .4 to .8 is suggested (for best reasoning/thinking), however it will still operate at much higher temps like 1.8, 2.6 etc.
 Depending on your prompt change temp SLOWLY: IE: .41,.42,.43 ... etc etc.