Instructions to use RemySkye/KAT-Coder-V2.5-Dev-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 RemySkye/KAT-Coder-V2.5-Dev-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 RemySkye/KAT-Coder-V2.5-Dev-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf RemySkye/KAT-Coder-V2.5-Dev-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 RemySkye/KAT-Coder-V2.5-Dev-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf RemySkye/KAT-Coder-V2.5-Dev-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 RemySkye/KAT-Coder-V2.5-Dev-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf RemySkye/KAT-Coder-V2.5-Dev-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 RemySkye/KAT-Coder-V2.5-Dev-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf RemySkye/KAT-Coder-V2.5-Dev-GGUF:Q4_K_M

Use Docker

docker model run hf.co/RemySkye/KAT-Coder-V2.5-Dev-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use RemySkye/KAT-Coder-V2.5-Dev-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "RemySkye/KAT-Coder-V2.5-Dev-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": "RemySkye/KAT-Coder-V2.5-Dev-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/RemySkye/KAT-Coder-V2.5-Dev-GGUF:Q4_K_M

Ollama
How to use RemySkye/KAT-Coder-V2.5-Dev-GGUF with Ollama:
```
ollama run hf.co/RemySkye/KAT-Coder-V2.5-Dev-GGUF:Q4_K_M
```

Unsloth Studio

How to use RemySkye/KAT-Coder-V2.5-Dev-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 RemySkye/KAT-Coder-V2.5-Dev-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 RemySkye/KAT-Coder-V2.5-Dev-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for RemySkye/KAT-Coder-V2.5-Dev-GGUF to start chatting

How to use RemySkye/KAT-Coder-V2.5-Dev-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf RemySkye/KAT-Coder-V2.5-Dev-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "RemySkye/KAT-Coder-V2.5-Dev-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use RemySkye/KAT-Coder-V2.5-Dev-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 RemySkye/KAT-Coder-V2.5-Dev-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 RemySkye/KAT-Coder-V2.5-Dev-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use RemySkye/KAT-Coder-V2.5-Dev-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf RemySkye/KAT-Coder-V2.5-Dev-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 "RemySkye/KAT-Coder-V2.5-Dev-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"

Docker Model Runner
How to use RemySkye/KAT-Coder-V2.5-Dev-GGUF with Docker Model Runner:
```
docker model run hf.co/RemySkye/KAT-Coder-V2.5-Dev-GGUF:Q4_K_M
```

Lemonade

How to use RemySkye/KAT-Coder-V2.5-Dev-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull RemySkye/KAT-Coder-V2.5-Dev-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.KAT-Coder-V2.5-Dev-GGUF-Q4_K_M

List all available models

lemonade list

KAT-Coder-V2.5-Dev-GGUF / README.md

RemySkye

Update README.md

75d453c verified 9 days ago

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	---
	license: apache-2.0
	library_name: llama.cpp
	pipeline_tag: text-generation
	base_model:
	- Kwaipilot/KAT-Coder-V2.5-Dev
	base_model_relation: quantized
	quantized_by: RemySkye
	tags:
	- gguf
	- llama.cpp
	- quantized
	- text-generation
	- code
	- coding
	- agentic-coding
	- mixture-of-experts
	- moe
	- qwen3.5
	- qwen3.6
	---

	# KAT-Coder-V2.5-Dev-GGUF

	GGUF files for [Kwaipilot/KAT-Coder-V2.5-Dev](https://huggingface.co/Kwaipilot/KAT-Coder-V2.5-Dev), including a BF16 reference GGUF and multiple `llama.cpp` quantizations.

	## What is included

	\| File \| Format \| Size \|
	\|---\|---:\|---:\|
	\| `KAT-Coder-V2.5-Dev-BF16.gguf` \| `BF16` \| 64.61 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q8_0.gguf` \| `Q8_0` \| 34.37 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q6_K.gguf` \| `Q6_K` \| 26.56 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q5_K_M.gguf` \| `Q5_K_M` \| 23.03 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q5_1.gguf` \| `Q5_1` \| 24.32 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q5_0.gguf` \| `Q5_0` \| 22.33 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q5_K_S.gguf` \| `Q5_K_S` \| 22.33 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q4_K_M.gguf` \| `Q4_K_M` \| 19.71 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q4_1.gguf` \| `Q4_1` \| 20.35 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q4_0.gguf` \| `Q4_0` \| 18.36 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q4_K_S.gguf` \| `Q4_K_S` \| 18.52 GiB \|
	\| `KAT-Coder-V2.5-Dev-IQ4_XS.gguf` \| `IQ4_XS` \| 17.64 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q3_K_L.gguf` \| `Q3_K_L` \| 16.87 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q3_K_M.gguf` \| `Q3_K_M` \| 15.61 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q3_K_S.gguf` \| `Q3_K_S` \| 14.14 GiB \|
	\| `KAT-Coder-V2.5-Dev-Q2_K.gguf` \| `Q2_K` \| 12.05 GiB \|

	All model behavior, intended use, limitations, and licensing originate from [Kwaipilot/KAT-Coder-V2.5-Dev](https://huggingface.co/Kwaipilot/KAT-Coder-V2.5-Dev).