Instructions to use KyleHessling1/Qwopus-GLM-18B-Merged-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use KyleHessling1/Qwopus-GLM-18B-Merged-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="KyleHessling1/Qwopus-GLM-18B-Merged-GGUF",
	filename="Qwopus-GLM-18B-Healed-Q3_K_M.gguf",
)

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

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use KyleHessling1/Qwopus-GLM-18B-Merged-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf KyleHessling1/Qwopus-GLM-18B-Merged-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf KyleHessling1/Qwopus-GLM-18B-Merged-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 KyleHessling1/Qwopus-GLM-18B-Merged-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf KyleHessling1/Qwopus-GLM-18B-Merged-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 KyleHessling1/Qwopus-GLM-18B-Merged-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf KyleHessling1/Qwopus-GLM-18B-Merged-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 KyleHessling1/Qwopus-GLM-18B-Merged-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf KyleHessling1/Qwopus-GLM-18B-Merged-GGUF:Q4_K_M

Use Docker

docker model run hf.co/KyleHessling1/Qwopus-GLM-18B-Merged-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use KyleHessling1/Qwopus-GLM-18B-Merged-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "KyleHessling1/Qwopus-GLM-18B-Merged-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": "KyleHessling1/Qwopus-GLM-18B-Merged-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/KyleHessling1/Qwopus-GLM-18B-Merged-GGUF:Q4_K_M

Ollama
How to use KyleHessling1/Qwopus-GLM-18B-Merged-GGUF with Ollama:
```
ollama run hf.co/KyleHessling1/Qwopus-GLM-18B-Merged-GGUF:Q4_K_M
```

Unsloth Studio new

How to use KyleHessling1/Qwopus-GLM-18B-Merged-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 KyleHessling1/Qwopus-GLM-18B-Merged-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 KyleHessling1/Qwopus-GLM-18B-Merged-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for KyleHessling1/Qwopus-GLM-18B-Merged-GGUF to start chatting

Pi new

How to use KyleHessling1/Qwopus-GLM-18B-Merged-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf KyleHessling1/Qwopus-GLM-18B-Merged-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": "KyleHessling1/Qwopus-GLM-18B-Merged-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use KyleHessling1/Qwopus-GLM-18B-Merged-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 KyleHessling1/Qwopus-GLM-18B-Merged-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 KyleHessling1/Qwopus-GLM-18B-Merged-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use KyleHessling1/Qwopus-GLM-18B-Merged-GGUF with Docker Model Runner:
```
docker model run hf.co/KyleHessling1/Qwopus-GLM-18B-Merged-GGUF:Q4_K_M
```

Lemonade

How to use KyleHessling1/Qwopus-GLM-18B-Merged-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull KyleHessling1/Qwopus-GLM-18B-Merged-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Qwopus-GLM-18B-Merged-GGUF-Q4_K_M

List all available models

lemonade list

KyleHessling1 commited on 25 days ago

Commit

c86409e

verified ·

1 Parent(s): 9d30958

Add frontend stress test results and sample files to model card

Browse files

Files changed (1) hide show

README.md +27 -0

README.md CHANGED Viewed

@@ -92,6 +92,33 @@ The raw frankenmerge had code formatting issues (garbled code blocks, missing br
 Three programming tests still fail on the healed version: one function naming issue, one missing JS paren, and one that doesn't produce a code block for pytest generation. These are residual formatting artifacts from the merge.
 ## Architecture
 | Property | Value |

 Three programming tests still fail on the healed version: one function naming issue, one missing JS paren, and one that doesn't produce a code block for pytest generation. These are residual formatting artifacts from the merge.
+## Frontend Code Generation — Stress Test Results
+We put the healed model through a rigorous frontend stress test: 6 increasingly complex HTML/CSS/JS generation tasks, each requiring thousands of tokens of structurally valid code output. The results speak for themselves:
+| Test | What We Asked For | Checks Passed | Output Size |
+|---|---|---|---|
+| Weather Dashboard | Responsive dashboard, CSS vars, dark mode toggle, 5-day forecast grid | **9/9** | 14.5K chars |
+| E-Commerce Product Page | Image gallery, color swatches, quantity selector, tabbed content, sticky mobile bar | **12/12** | 16.7K chars |
+| Animated SaaS Landing | Moving gradient, typing animation, IntersectionObserver scroll reveals, auto-rotating testimonial carousel, 3 pricing tiers | **13/13** | 24.1K chars |
+| Analytics Dashboard | SVG bar chart with tooltips, SVG donut chart, sortable data table, collapsible sidebar, dark theme | **13/13** | 22.3K chars |
+| Multi-Step Registration | 3-step form wizard, real-time validation, password strength meter, state dropdown, animated transitions, success modal | **12/12** | 23.3K chars |
+| Snake Game | Canvas game loop, arrow key controls, collision detection, localStorage high score, increasing difficulty | **11/12** | 11.2K chars |
+**62/63 total checks passed (98.4%)**
+Every single output had:
+- **Perfectly balanced CSS braces** (zero imbalance across all 6 files)
+- **Perfectly balanced JS parentheses** (zero imbalance across all 6 files)
+- **Zero garbled or hallucinated text**
+- **Working JavaScript** — dark mode toggles, IntersectionObserver animations, SVG chart rendering, form validation, canvas game loops
+The only miss: the Snake game had a minor closing tag typo (`html>` instead of `</html>`) at the very end.
+This is remarkable for a frankenmerge of two 9B models with only 1000 steps of QLoRA healing. The model is producing **production-quality frontend code** — not just syntactically valid HTML, but sophisticated interactive applications with modern CSS (Grid, Flexbox, custom properties, keyframe animations) and non-trivial JavaScript (IntersectionObserver, requestAnimationFrame game loops, real-time form validation, SVG chart generation).
+All 6 sample HTML files are included in the `samples/` directory of this repo — download them and open in a browser to see for yourself.
 ## Architecture
 | Property | Value |