Instructions to use YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S 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 YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S 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 YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S # Run inference directly in the terminal: llama cli -hf YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S # Run inference directly in the terminal: llama cli -hf YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S # Run inference directly in the terminal: ./build/bin/llama cli -hf YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S
Use Docker
docker model run hf.co/YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S
- Llama new
- LM Studio
- Jan
- vLLM
How to use YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S
- Ollama
How to use YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S with Ollama:
ollama run hf.co/YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S
- Unsloth Desktop
- Pi
How to use YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S
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": "YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S with Docker Model Runner:
docker model run hf.co/YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S
- Lemonade
How to use YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S
Run and chat with the model
lemonade run user.Qwopus3.5-27B-v3-Abliterated-TQ3_4S-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S
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 YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S
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 "YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S" \ --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"
Qwopus3.5-27B-v3-Abliterated-TQ3_4S
TQ3_4S is a 3.5-bit Walsh-Hadamard-transform weight format with four per-8 scales per 32-weight block.
This release is a TQ3_4S GGUF quantization of croll83/Qwopus3.5-27B-v3-Abliterated, derived from the Qwen3.5-27B family.
Quantization Source
- HF source checkout:
croll83/Qwopus3.5-27B-v3-Abliterated
- upstream family:
Qwen/Qwen3.5-27B
- F16 GGUF used as the quantization source:
Qwopus3.5-27B-v3-Abliterated-f16.gguf
Quantized with:
./build/bin/llama-quantize --pure \
/path/to/Qwopus3.5-27B-v3-Abliterated-f16.gguf \
/path/to/Qwopus3.5-27B-v3-Abliterated-TQ3_4S.gguf \
TQ3_4S \
16
Runtime Validation
Validated on public llama.cpp-tq3:
- runtime repo:
turbo-tan/llama.cpp-tq3
- LM Studio setup:
- no-thinking server smoke:
- runtime:
llama-server --reasoning off - prompt:
Write ONLY the word ok. - response:
ok
- runtime:
Example
./build/bin/llama-simple-chat \
-m /path/to/Qwopus3.5-27B-v3-Abliterated-TQ3_4S.gguf \
-ngl 99 -c 2048
Server example:
./build/bin/llama-server \
-m /path/to/Qwopus3.5-27B-v3-Abliterated-TQ3_4S.gguf \
--host 127.0.0.1 --port 8080 \
-ngl 99 -c 8192 -np 1 \
-ctk q8_0 -ctv q8_0 -fa on \
--no-warmup --jinja
Notes
- This is a weight quantization release.
- The source repo includes
Qwopus3.5-27B-v3-Abliterated-mmproj.gguf. - Upload
mmproj.ggufalongside this model if you want to preserve the same multimodal packaging. - Running this GGUF requires
TQ3_4Sruntime support fromturbo-tan/llama.cpp-tq3.
Credits
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We're not able to determine the quantization variants.
Model tree for YTan2000/Qwopus3.5-27B-v3-Abliterated-TQ3_4S
Base model
Qwen/Qwen3.5-27B