Instructions to use michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF", filename="Qwopus3.6-27B-Coder-MTP-NVFP4-TURBO.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 michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-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 michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4 # Run inference directly in the terminal: llama cli -hf michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4 # Run inference directly in the terminal: llama cli -hf michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4
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 michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4 # Run inference directly in the terminal: ./llama-cli -hf michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4
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 michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4 # Run inference directly in the terminal: ./build/bin/llama-cli -hf michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4
Use Docker
docker model run hf.co/michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4
- LM Studio
- Jan
- Ollama
How to use michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF with Ollama:
ollama run hf.co/michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4
- Unsloth Studio
How to use michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-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 michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-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 michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF to start chatting
- Pi
How to use michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4
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": "michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-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 michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4
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 michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4
Run Hermes
hermes
- Atomic Chat new
- Docker Model Runner
How to use michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF with Docker Model Runner:
docker model run hf.co/michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4
- Lemonade
How to use michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF:NVFP4
Run and chat with the model
lemonade run user.Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF-NVFP4
List all available models
lemonade list
Qwen3.6-35B-A3B-NVFP4-MTP-GGUF
This repo contains two experimental NVFP4 GGUF quantizations of Jackrong's excellent Qwopus3.6-27-Coder for llama.cpp.
This was quantized using my experimental advanced-gguf-quantizer tool.
This model did not have any imatrix used with it, to better keep with the original model's finetuning done by Jackrong.
This repository contains two NVFP4 variants:
| Variant | File | Best for | Notes |
|---|---|---|---|
| TURBO | Qwopus3.6-27B-Coder-MTP-NVFP4-TURBO.gguf |
Max speed | More NVFP4. Lower quality metrics. |
| HQ | Qwopus3.6-27B-Coder-MTP-NVFP4-HQ.gguf |
Better quality | More tensors promoted. Slightly slower. |
Quality & Speed Results
All PPL/KLD results were measured against the same BF16 wikitest KLD base.
| Metric | TURBO | HQ | BF16 |
|---|---|---|---|
| Size | 15.12 GB | 16.98 GB | 51 GB |
| Ppl Ratio | 1.0348 | 1.031 | 1.000 |
| Mean KLD | 0.0414 | 0.0379 | 1.000 |
| Same Top p | 91.62% | 92.03% | 100% |
| pp512 | 5402.97 tk/s | 5104.84 tk/s | - |
| tg128 | 83.44 tk/s | 76.38 tk/s | - |
Evaluation Results
Further evaluation tests are underway to identify real world performance differences between TURBO and HQ.
| Benchmark | Samples | TURBO | HQ |
|---|---|---|---|
| GSM8K | - | -% | -% |
| HellaSwag | - | -% | -% |
| HumanEval | - | -% | -% |
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Model tree for michaelw9999/Qwopus3.6-27B-Coder-MTP-NVFP4-GGUF
Base model
Jackrong/Qwopus3.6-27B-v2