Instructions to use mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF",
	filename="Qwopus3.6-35B-A3B-Coder-APEX-Balanced.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 mudler/Qwopus3.6-35B-A3B-Coder-APEX-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 mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF
# Run inference directly in the terminal:
llama cli -hf mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF
# Run inference directly in the terminal:
llama cli -hf mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF

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 mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF
# Run inference directly in the terminal:
./llama-cli -hf mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF

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 mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF
# Run inference directly in the terminal:
./build/bin/llama-cli -hf mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF

Use Docker

docker model run hf.co/mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF

LM Studio
Jan
Ollama
How to use mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF with Ollama:
```
ollama run hf.co/mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF
```

Unsloth Studio

How to use mudler/Qwopus3.6-35B-A3B-Coder-APEX-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 mudler/Qwopus3.6-35B-A3B-Coder-APEX-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 mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF to start chatting

How to use mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF

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": "mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use mudler/Qwopus3.6-35B-A3B-Coder-APEX-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 mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF

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 mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF

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 "mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF" \
  --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 mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF with Docker Model Runner:
```
docker model run hf.co/mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF
```

Lemonade

How to use mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF

Run and chat with the model

lemonade run user.Qwopus3.6-35B-A3B-Coder-APEX-GGUF-{{QUANT_TAG}}

List all available models

lemonade list

mudler commited on 18 days ago

Commit

a500946

verified ·

1 Parent(s): 7a33537

Upload README.md with huggingface_hub

Browse files

Files changed (1) hide show

README.md +71 -0

README.md ADDED Viewed

	@@ -0,0 +1,71 @@

+---
+license: apache-2.0
+base_model: Jackrong/Qwopus3.6-35B-A3B-Coder
+tags:
+  - gguf
+  - quantized
+  - apex
+  - moe
+  - mixture-of-experts
+  - qwen3
+  - vlm
+  - vision
+  - coder
+  - code
+---
+<!-- apex-banner-v2 -->
+<div style="background-color: #f59e0b; color: white; padding: 20px; border-radius: 10px; text-align: center; margin: 20px 0;">
+<h2 style="color: white; margin: 0 0 10px 0;">⚡ Each donation = another big MoE quantized</h2>
+<p style="font-size: 18px; margin: 0 0 15px 0;">I host <b>30+ free APEX MoE quantizations</b> as independent research. My only local hardware is an <b>NVIDIA DGX Spark</b> (122 GB unified memory) — enough for ~30-50B-class MoEs, but <b>bigger ones (200B+) require rented compute</b> on H100/H200/Blackwell, typically $20-100 per quant.<br>If APEX quants are useful to you, your support directly funds those bigger runs.</p>
+<p style="font-size: 20px; margin: 0;">
+<a href="https://www.patreon.com/cw/mudler" style="color: white; text-decoration: underline;">🎉 Patreon (Monthly)</a> &nbsp;|&nbsp;
+<a href="https://www.buymeacoffee.com/mudler" style="color: white; text-decoration: underline;">☕ Buy Me a Coffee</a> &nbsp;|&nbsp;
+<a href="https://github.com/sponsors/mudler" style="color: white; text-decoration: underline;">⭐ GitHub Sponsors</a>
+</p>
+</div>
+# Qwopus3.6-35B-A3B-Coder — APEX GGUF
+**APEX (Adaptive Precision for EXpert Models)** quantizations of [Jackrong/Qwopus3.6-35B-A3B-Coder](https://huggingface.co/Jackrong/Qwopus3.6-35B-A3B-Coder) — a Qwen3.6-35B-A3B MoE tuned for coding.
+**Brought to you by the [LocalAI](https://github.com/mudler/LocalAI) team** | [APEX Project](https://github.com/mudler/apex-quant) | [Technical Report](https://github.com/mudler/apex-quant/blob/main/paper/APEX_Technical_Report.pdf)
+> This model ships an MTP head — for self-speculative decoding out of the box, see the MTP-bundled repo: [mudler/Qwopus3.6-35B-A3B-Coder-APEX-MTP-GGUF](https://huggingface.co/mudler/Qwopus3.6-35B-A3B-Coder-APEX-MTP-GGUF).
+## Available Files
+| File | Profile | Best For |
+|------|---------|----------|
+| Qwopus3.6-35B-A3B-Coder-APEX-I-Balanced.gguf | I-Balanced | Best overall — imatrix-enhanced |
+| Qwopus3.6-35B-A3B-Coder-APEX-I-Quality.gguf | I-Quality | Highest quality with imatrix |
+| Qwopus3.6-35B-A3B-Coder-APEX-Quality.gguf | Quality | Highest quality (no imatrix) |
+| Qwopus3.6-35B-A3B-Coder-APEX-Balanced.gguf | Balanced | General purpose |
+| Qwopus3.6-35B-A3B-Coder-APEX-I-Compact.gguf | I-Compact | Consumer GPUs, imatrix-enhanced |
+| Qwopus3.6-35B-A3B-Coder-APEX-Compact.gguf | Compact | Consumer GPUs |
+| Qwopus3.6-35B-A3B-Coder-APEX-I-Mini.gguf | I-Mini | Smallest viable, fastest inference |
+| mmproj.gguf | Vision projector | Required for image understanding |
+## What is APEX?
+APEX is a quantization strategy for Mixture-of-Experts (MoE) models. It classifies tensors by role (routed expert, shared expert, attention) and applies a layer-wise precision gradient — edge layers (first/last 5) get higher precision, middle layers get more aggressive compression. I-variants use diverse imatrix calibration (chat, code, reasoning, tool-calling, agentic traces, Wikipedia).
+See the [APEX project](https://github.com/mudler/apex-quant) for full details.
+## Architecture
+- **Model**: Qwopus3.6-35B-A3B-Coder (Qwen3_5MoeForConditionalGeneration, Qwen3.6-35B-A3B base)
+- **Layers**: 40 · **Experts**: 256 routed + 1 shared (8 active) · **Total/Active**: ~35B / ~3B
+- **Attention**: Hybrid (full attention every 4th layer, linear otherwise)
+- **Vision**: Built-in vision encoder (mmproj included)
+- **Calibration**: v1.3 diverse dataset
+## Run with LocalAI
+```bash
+local-ai run mudler/Qwopus3.6-35B-A3B-Coder-APEX-GGUF@Qwopus3.6-35B-A3B-Coder-APEX-I-Balanced.gguf
+```
+## Credits
+APEX is brought to you by the [LocalAI](https://github.com/mudler/LocalAI) team. Built on [llama.cpp](https://github.com/ggerganov/llama.cpp). Base model by [Jackrong](https://huggingface.co/Jackrong).