Instructions to use OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF 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 OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-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 OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-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 OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-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 OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M
Use Docker
docker model run hf.co/OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-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": "OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M
- Ollama
How to use OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF with Ollama:
ollama run hf.co/OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M
- Unsloth Studio
How to use OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-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 OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-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 OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF to start chatting
- Pi
How to use OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-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": "OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M
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 "OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M" \ --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 OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF with Docker Model Runner:
docker model run hf.co/OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M
- Lemonade
How to use OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-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 OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-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 OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
Support & Community
☕ If these models are useful to you, consider supporting my work — it funds compute for more & larger abliterations.
💬 Discord: discord.gg/rhUZY5GEZr · ₿ Bitcoin: bc1qsvfduzj9fjs9fugpc52yver3f2g8fp7xjxecdv
Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated — GGUF
Overview
GGUF build of OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated. See the parent repo for the full pipeline: refusal ablation → constrained-LoRA Opus reasoning SFT → unconstrained chosen-completion SFT → Kimi K2.6 reasoning DPO (≈3,000 distilled samples + synthetic data, improving reasoning verbosity on ~12% of requests and removing looping on 2–6% of long-tail conversations).
This repo ships both the language model and the vision projector (mmproj), so it runs as a full multimodal (image + text) model in llama.cpp / LM Studio.
Files
| File | Bits/weight | Size | Notes |
|---|---|---|---|
Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-Q4_K_M.gguf |
~4.6 | ~76 GB | Language model. Q4_K_M keeps output.weight at higher precision. MTP head included. |
mmproj-Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-F16.gguf |
F16 | ~0.9 GB | Vision projector (qwen3vl_merger, Qwen3.5 vision tower). Load alongside the model for image input. |
Vision (mmproj)
Pass the mmproj file to enable image input. The vision tower is the standard Qwen3.5-122B-A10B Qwen3-VL encoder (carried over unchanged from the base model), F16.
# llama.cpp multimodal CLI
llama-mtmd-cli \
-m Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-Q4_K_M.gguf \
--mmproj mmproj-Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-F16.gguf \
--image path/to/image.jpg \
-p "Describe this image." -ngl 99
In LM Studio: keep the mmproj-*.gguf in the same folder as the model — it is detected automatically and the image-attachment button becomes available.
MTP (multi-token prediction)
This build keeps the MTP head (blk.48.nextn.*, qwen35moe.nextn_predict_layers). Recent llama.cpp with qwen35moe MTP support (e.g. LM Studio's llama.cpp 2.15.0) can load it and expose "MTP Speculative Decoding" in the advanced load settings.
⚠️ Caveat: in our testing the MTP head gave no measurable performance gain on this checkpoint. It is shipped for completeness and would need to be retrained to be genuinely useful — happy to do so if there is interest in the model. The model runs fine with MTP speculative decoding off.
Usage (text-only)
Requires a recent llama.cpp build that supports the qwen35moe architecture (Gated DeltaNet linear-attn + MoE).
llama-cli -m Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-Q4_K_M.gguf \
-p "Explain why the sky is blue." -ngl 99 -c 8192
Hardware
Q4_K_M (76 GB) + mmproj (0.9 GB) fits on a single 96 GB GPU, an Apple Silicon machine with ≥ 96 GB unified memory, or CPU + RAM. Leave headroom for KV cache / context.
Notes
- License: Other (inherits from the Qwen3.5 base license)
- Parent (full weights): Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated
- Modality: Text + Vision (via
mmproj) + MTP head (see caveat) - Architecture: Qwen3 MoE (~10B active / 122B total) + Qwen3-VL vision tower
Disclaimer
Use is the responsibility of the user. Ensure your usage complies with applicable laws, platform rules, and deployment requirements.
- Downloads last month
- 83,056
4-bit
Model tree for OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destill-healed-abliterated-GGUF
Base model
Qwen/Qwen3.5-122B-A10B