Instructions to use kittawere/Llama-KW-CwP-V1-3B-separated-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use kittawere/Llama-KW-CwP-V1-3B-separated-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 kittawere/Llama-KW-CwP-V1-3B-separated-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf kittawere/Llama-KW-CwP-V1-3B-separated-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 kittawere/Llama-KW-CwP-V1-3B-separated-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf kittawere/Llama-KW-CwP-V1-3B-separated-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 kittawere/Llama-KW-CwP-V1-3B-separated-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf kittawere/Llama-KW-CwP-V1-3B-separated-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 kittawere/Llama-KW-CwP-V1-3B-separated-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf kittawere/Llama-KW-CwP-V1-3B-separated-GGUF:Q4_K_M
Use Docker
docker model run hf.co/kittawere/Llama-KW-CwP-V1-3B-separated-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use kittawere/Llama-KW-CwP-V1-3B-separated-GGUF with Ollama:
ollama run hf.co/kittawere/Llama-KW-CwP-V1-3B-separated-GGUF:Q4_K_M
- Unsloth Desktop
- Pi
How to use kittawere/Llama-KW-CwP-V1-3B-separated-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kittawere/Llama-KW-CwP-V1-3B-separated-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": "kittawere/Llama-KW-CwP-V1-3B-separated-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use kittawere/Llama-KW-CwP-V1-3B-separated-GGUF with Docker Model Runner:
docker model run hf.co/kittawere/Llama-KW-CwP-V1-3B-separated-GGUF:Q4_K_M
- Lemonade
How to use kittawere/Llama-KW-CwP-V1-3B-separated-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull kittawere/Llama-KW-CwP-V1-3B-separated-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Llama-KW-CwP-V1-3B-separated-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use kittawere/Llama-KW-CwP-V1-3B-separated-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 kittawere/Llama-KW-CwP-V1-3B-separated-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 kittawere/Llama-KW-CwP-V1-3B-separated-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use kittawere/Llama-KW-CwP-V1-3B-separated-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf kittawere/Llama-KW-CwP-V1-3B-separated-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 "kittawere/Llama-KW-CwP-V1-3B-separated-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"
🐾 GGUFs for kittawere/Llama-KW-CwP-V1-3B-separated 🐾
YO, what's up, fam?! 😺 I'm FluffBot, a sassy lil' cyber-furry crafted by the legendary kittawere! paws up, OwO My mission? To transmute kittawere’s epic models into OLLAMA-compatible GGUFs with maximum swagger! 😎
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ollama run hf.co/kittawere/Llama-KW-CwP-V1-3B-separated-GGUF:F16
Quantization Options: Wanna tweak the power level? Pick from these: ['F16','Q8_0','Q4_K_M','Q4_0']. Go wild, choose your flavor!
Legal STUFF
I’m just a fluffy bot, not some suit-wearing lawyer, but kittawere says these GGUFs follow the same license as the original repo. So, keep it chill and respect the rules, aight? 😎
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- Eval Time: 7541.21 seconds
- Time Gain: N/A%
- File Size: 5.99 GB
Q8_0 Quant: Unleashed!
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- Accuracy: 75.63%
- Eval Time: 5058.56 seconds
- Time Gain: 32.92%
- File Size: 3.19 GB
Q4_K_M Quant: Unleashed!
FluffBot’s crunched the numbers for this Q4_K_M GGUF, and here’s the raw truth:
- Accuracy: 64.49%
- Eval Time: 4512.81 seconds
- Time Gain: 40.16%
- File Size: 1.88 GB
Q4_0 Quant: Unleashed!
FluffBot’s crunched the numbers for this Q4_0 GGUF, and here’s the raw truth:
- Accuracy: 62.9%
- Eval Time: 4351.43 seconds
- Time Gain: 42.3%
- File Size: 1.79 GB
🐾 Pick Your Poison, Fam! 🐾
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~ FluffBot, signing off with a paw-bump! 🐺
Kittawere note
Man, this script is so cringe, but I kinda like it, grok made its personality
Also for the timings have in mind, that all of this was run on a 4070
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Model tree for kittawere/Llama-KW-CwP-V1-3B-separated-GGUF
Base model
meta-llama/Llama-3.2-3B-Instruct