Instructions to use Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop 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 Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16
# Run inference directly in the terminal:
llama cli -hf Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16
# Run inference directly in the terminal:
llama cli -hf Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16

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 Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16
# Run inference directly in the terminal:
./llama-cli -hf Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16

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 Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16

Use Docker

docker model run hf.co/Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16

LM Studio
Jan
Ollama
How to use Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop with Ollama:
```
ollama run hf.co/Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16
```
Unsloth Desktop

How to use Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop with Docker Model Runner:
```
docker model run hf.co/Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16
```

Lemonade

How to use Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16

Run and chat with the model

lemonade run user.gguf-f16-Qwen3.6-35B-A3B-AntiLoop-F16

List all available models

lemonade list

Hermes Agent

How to use Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16

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 Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16

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 "Felladrin/gguf-f16-Qwen3.6-35B-A3B-AntiLoop:F16" \
  --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"

gguf-f16-Qwen3.6-35B-A3B-AntiLoop / README.md

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metadata

license: apache-2.0
license_link: >-
  https://huggingface.co/Qwen/Qwen3.6-35B-A3B/blob/995ad96eacd98c81ed38be0c5b274b04031597b0/LICENSE
base_model: N8Programs/Qwen3.6-35B-A3B-AntiLoop
tags:
  - gguf
  - llama.cpp
  - qwen3.6
  - moe
quantized_by: Felladrin

gguf-f16-Qwen3.6-35B-A3B-AntiLoop

GGUF conversion of N8Programs/Qwen3.6-35B-A3B-AntiLoop, produced with llama.cpp's convert_hf_to_gguf.py.

Qwen3.6-35B-A3B-AntiLoop-F16.gguf — full-precision (F16) text-model GGUF, unquantized, suitable as a base for further quantization (e.g. with llama-quantize). The multi-token-prediction (MTP) head is bundled in.
mmproj-BF16.gguf — multimodal projector (vision tower) for image input, in BF16, matching the source checkpoint's native tensor dtype. Use alongside the text GGUF for vision support (e.g. llama-server ... --mmproj mmproj-BF16.gguf).

See the source model card for benchmarks, training details, license terms, and usage notes.