Instructions to use QuantFactory/Qwen2.5-14B_Uncencored_Instruct-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 QuantFactory/Qwen2.5-14B_Uncencored_Instruct-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 QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/Qwen2.5-14B_Uncencored_Instruct-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 QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf QuantFactory/Qwen2.5-14B_Uncencored_Instruct-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 QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf QuantFactory/Qwen2.5-14B_Uncencored_Instruct-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 QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M

Use Docker

docker model run hf.co/QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "QuantFactory/Qwen2.5-14B_Uncencored_Instruct-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": "QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M

Ollama
How to use QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF with Ollama:
```
ollama run hf.co/QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M
```
Unsloth Desktop

How to use QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF with Docker Model Runner:
```
docker model run hf.co/QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M
```

Lemonade

How to use QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qwen2.5-14B_Uncencored_Instruct-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF:Q4_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

aashish1904 commited on Sep 21, 2024

Commit

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	@@ -0,0 +1,59 @@

+---
+license: apache-2.0
+language:
+- en
+pipeline_tag: text-generation
+---
+[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
+# QuantFactory/Qwen2.5-14B_Uncencored_Instruct-GGUF
+This is quantized version of [SicariusSicariiStuff/Qwen2.5-14B_Uncencored_Instruct](https://huggingface.co/SicariusSicariiStuff/Qwen2.5-14B_Uncencored_Instruct) created using llama.cpp
+# Original Model Card
+<div align="center">
+  <b style="font-size: 40px;">Qwen2.5-14B_Uncencored Instruct</b>
+</div>
+<img src="https://huggingface.co/SicariusSicariiStuff/Phi-3.5-mini-instruct_Uncensored/resolve/main/Misc/Uncensored.png" alt="Uncensored.png" style="width: 90%; min-width: 500px; display: block; margin: auto;">
+This is the instruct model, except my uncensoring protocol I also added some RP data, Story writing and tried to nudge the model towards aggressiveness, for more spicy RP and story bias. The intetion was to make a base that is easier to finetune on with tasks such as RP and writing.
+# Model Details
+- Censorship level: <b>pending</b>
+- **pending** / 10 (10 completely uncensored)
+- UGI score: SOON
+### Support
+<img src="https://i.imgur.com/0lHHN95.png" alt="GPUs too expensive" style="width: 10%; min-width: 100px; display: block; margin: left;">
+- [My Ko-fi page](https://ko-fi.com/sicarius) ALL donations will go for research resources and compute, every bit is appreciated 🙏🏻
+## Other stuff
+- [Blog and updates](https://huggingface.co/SicariusSicariiStuff/Blog_And_Updates) Some updates, some rambles, sort of a mix between a diary and a blog.
+- [LLAMA-3_8B_Unaligned](https://huggingface.co/SicariusSicariiStuff/LLAMA-3_8B_Unaligned) The grand project that started it all.