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
- llama.cpp
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
- Pi
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"
Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- Qwen3.6-35B-A3B-AntiLoop-F16.gguf +3 -0
- README.md +19 -0
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---
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license: apache-2.0
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license_link: https://huggingface.co/Qwen/Qwen3.6-35B-A3B/blob/995ad96eacd98c81ed38be0c5b274b04031597b0/LICENSE
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base_model: N8Programs/Qwen3.6-35B-A3B-AntiLoop
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tags:
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- gguf
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- llama.cpp
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- qwen3.6
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- moe
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quantized_by: Felladrin
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---
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# gguf-f16-Qwen3.6-35B-A3B-AntiLoop
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GGUF F16 conversion of [N8Programs/Qwen3.6-35B-A3B-AntiLoop](https://huggingface.co/N8Programs/Qwen3.6-35B-A3B-AntiLoop), produced with [llama.cpp](https://github.com/ggml-org/llama.cpp)'s `convert_hf_to_gguf.py`.
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This is the 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. The vision tower present in the source checkpoint is not included in this conversion.
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See the source model card for benchmarks, training details, license terms, and usage notes.
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