Instructions to use DJLougen/Qwable-5-27B-Coder-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DJLougen/Qwable-5-27B-Coder-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="DJLougen/Qwable-5-27B-Coder-GGUF",
	filename="Qwable-5-27B-Coder-IQ1_S.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use DJLougen/Qwable-5-27B-Coder-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 DJLougen/Qwable-5-27B-Coder-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf DJLougen/Qwable-5-27B-Coder-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 DJLougen/Qwable-5-27B-Coder-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf DJLougen/Qwable-5-27B-Coder-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 DJLougen/Qwable-5-27B-Coder-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf DJLougen/Qwable-5-27B-Coder-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 DJLougen/Qwable-5-27B-Coder-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf DJLougen/Qwable-5-27B-Coder-GGUF:Q4_K_M

Use Docker

docker model run hf.co/DJLougen/Qwable-5-27B-Coder-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use DJLougen/Qwable-5-27B-Coder-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DJLougen/Qwable-5-27B-Coder-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": "DJLougen/Qwable-5-27B-Coder-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/DJLougen/Qwable-5-27B-Coder-GGUF:Q4_K_M

Ollama
How to use DJLougen/Qwable-5-27B-Coder-GGUF with Ollama:
```
ollama run hf.co/DJLougen/Qwable-5-27B-Coder-GGUF:Q4_K_M
```

Unsloth Studio

How to use DJLougen/Qwable-5-27B-Coder-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 DJLougen/Qwable-5-27B-Coder-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 DJLougen/Qwable-5-27B-Coder-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for DJLougen/Qwable-5-27B-Coder-GGUF to start chatting

How to use DJLougen/Qwable-5-27B-Coder-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf DJLougen/Qwable-5-27B-Coder-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": "DJLougen/Qwable-5-27B-Coder-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use DJLougen/Qwable-5-27B-Coder-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 DJLougen/Qwable-5-27B-Coder-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 DJLougen/Qwable-5-27B-Coder-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use DJLougen/Qwable-5-27B-Coder-GGUF with Docker Model Runner:
```
docker model run hf.co/DJLougen/Qwable-5-27B-Coder-GGUF:Q4_K_M
```

Lemonade

How to use DJLougen/Qwable-5-27B-Coder-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull DJLougen/Qwable-5-27B-Coder-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qwable-5-27B-Coder-GGUF-Q4_K_M

List all available models

lemonade list

DJLougen commited on 9 days ago

Commit

763ee7d

verified ·

1 Parent(s): 9b24d2e

Redesign GGUF model card

Browse files

Files changed (1) hide show

README.md +5 -24

README.md CHANGED Viewed

@@ -28,13 +28,17 @@ tags:
   <img src="./assets/banner.jpeg" alt="Qwable-5-27B-Coder banner" style="width:100%;max-width:1024px;border-radius:18px;" />
 </p>
 # Qwable-5-27B-Coder-GGUF
 **Qwable-5-27B-Coder-GGUF** packages the Qwable coder-agent tune for llama.cpp, Ollama, and local workstation inference. It comes from a Qwen3.6-based model trained first on **Claude Fable 5 traces**, then continued on **Kimi 2.7 Coder traces**.
 Use this repo when you want Qwable's coding-agent behavior in GGUF form: repository inspection, patch planning, terminal feedback, verifier recovery, and long-context coding prompts.
-Training, quantization, and coder-agent evaluation are expensive. If Qwable helps your work, support continued releases at **[ko-fi.com/djlougen](https://ko-fi.com/djlougen)**.
 ## Quant menu
@@ -95,23 +99,6 @@ hf download DJLougen/Qwable-5-27B-Coder-GGUF \
   --local-dir .
 ```
-Use the server with an OpenAI-compatible client:
-```python
-from openai import OpenAI
-client = OpenAI(base_url="http://localhost:8080/v1", api_key="not-needed")
-resp = client.chat.completions.create(
-    model="Qwable-5-27B-Coder-GGUF",
-    messages=[
-        {"role": "system", "content": "You are Qwable, a precise coding agent."},
-        {"role": "user", "content": "Find the likely bug in this failing test output and propose a patch."},
-    ],
-)
-print(resp.choices[0].message.content)
-```
 ## Choosing a file
 - Start with `Q4_K_M` unless you are explicitly testing quality ceilings or memory floors.
@@ -119,12 +106,6 @@ print(resp.choices[0].message.content)
 - Use `IQ1_S` only when the model otherwise will not fit; verify quality on your own tasks.
 - Keep prompts concrete: include repository context, exact errors, constraints, and verifier commands.
-Suggested system prompt:
-```text
-You are Qwable, a precise coding agent. Inspect before editing. Prefer minimal, correct patches. Preserve existing conventions. Verify behavior with the narrowest meaningful test before finalizing.
-```
 ## Related releases
 - Source BF16 Transformers checkpoint: [`DJLougen/Qwable-5-27B-Coder`](https://huggingface.co/DJLougen/Qwable-5-27B-Coder)

   <img src="./assets/banner.jpeg" alt="Qwable-5-27B-Coder banner" style="width:100%;max-width:1024px;border-radius:18px;" />
 </p>
+<p align="center">
+  <img src="./assets/trace-board.svg" alt="Qwable GGUF quant runway" style="width:100%;max-width:1100px;border-radius:22px;" />
+</p>
 # Qwable-5-27B-Coder-GGUF
 **Qwable-5-27B-Coder-GGUF** packages the Qwable coder-agent tune for llama.cpp, Ollama, and local workstation inference. It comes from a Qwen3.6-based model trained first on **Claude Fable 5 traces**, then continued on **Kimi 2.7 Coder traces**.
 Use this repo when you want Qwable's coding-agent behavior in GGUF form: repository inspection, patch planning, terminal feedback, verifier recovery, and long-context coding prompts.
+<a href="https://ko-fi.com/djlougen"><img alt="Support on Ko-fi" src="https://img.shields.io/badge/Support%20the%20compute-Ko--fi-ff5f5f?style=for-the-badge&logo=kofi&logoColor=white"></a>
 ## Quant menu
   --local-dir .
 ```
 ## Choosing a file
 - Start with `Q4_K_M` unless you are explicitly testing quality ceilings or memory floors.
 - Use `IQ1_S` only when the model otherwise will not fit; verify quality on your own tasks.
 - Keep prompts concrete: include repository context, exact errors, constraints, and verifier commands.
 ## Related releases
 - Source BF16 Transformers checkpoint: [`DJLougen/Qwable-5-27B-Coder`](https://huggingface.co/DJLougen/Qwable-5-27B-Coder)