Instructions to use 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="4569DEGENS/qwopus-typescript-react-expert-v1-GGUF",
	filename="qwopus-edgepoint-Q4_K_M.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf 4569DEGENS/qwopus-typescript-react-expert-v1-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 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf 4569DEGENS/qwopus-typescript-react-expert-v1-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 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF:Q4_K_M

Use Docker

docker model run hf.co/4569DEGENS/qwopus-typescript-react-expert-v1-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF with Ollama:
```
ollama run hf.co/4569DEGENS/qwopus-typescript-react-expert-v1-GGUF:Q4_K_M
```

Unsloth Studio

How to use 4569DEGENS/qwopus-typescript-react-expert-v1-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 4569DEGENS/qwopus-typescript-react-expert-v1-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 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF to start chatting

How to use 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf 4569DEGENS/qwopus-typescript-react-expert-v1-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": "4569DEGENS/qwopus-typescript-react-expert-v1-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf 4569DEGENS/qwopus-typescript-react-expert-v1-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 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF with Docker Model Runner:
```
docker model run hf.co/4569DEGENS/qwopus-typescript-react-expert-v1-GGUF:Q4_K_M
```

Lemonade

How to use 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.qwopus-typescript-react-expert-v1-GGUF-Q4_K_M

List all available models

lemonade list

Qwopus TypeScript/React Expert v1 - GGUF

Fine-tuned Qwopus 3.6 27B v2 specialized for full-stack TypeScript/React/Express/Mongoose development.

Trained on 4,919 high-quality examples covering:

Full-stack patterns & refactors
React hooks & components
Express + Mongoose backends
Socket.IO real-time systems
Animations (Framer Motion, GSAP, Reanimated)
Responsive design
End-to-end verification
Testing, Migration, Performance
Security & architecture

Quantizations

File	Size	Use Case
Q4_K_M	~16GB	Recommended for Mac (M1/M2/M3/M4)
Q5_K_M	~19GB	Higher quality, slower
Q8_0	~28GB	Near-lossless quality

Usage with llama.cpp / LM Studio / Ollama

# llama.cpp
./llama-cli -m qwopus-edgepoint-Q4_K_M.gguf -p "Your prompt"

# LM Studio - just open the GGUF file
# Ollama - import via Modelfile

Training Details

Base: Qwopus 3.6 27B v2
Method: QLoRA (rank 128, alpha 256)
Hardware: 1x H200
Dataset: 4,919 examples, 17 domains
Context: 8192 tokens
Epochs: 2

Dataset

Open-source dataset available at: https://github.com/ReuvenDagaga/LLM

Citation

@misc{qwopus-typescript-react-expert-v1,
  author = {Reuven Dagaga},
  title = {Qwopus TypeScript/React Expert v1},
  year = {2026},
  howpublished = {HuggingFace},
  url = {https://huggingface.co/4569DEGENS/qwopus-typescript-react-expert-v1-GGUF}
}

Downloads last month: 185

GGUF

Model size

27B params

Architecture

qwen35

Hardware compatibility

4-bit

5-bit

8-bit

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Model tree for 4569DEGENS/qwopus-typescript-react-expert-v1-GGUF

Base model

Jackrong/Qwopus3.6-27B-v2

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