Instructions to use havenoammo/Qwen3.6-35B-A3B-MTP-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use havenoammo/Qwen3.6-35B-A3B-MTP-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="havenoammo/Qwen3.6-35B-A3B-MTP-GGUF")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("havenoammo/Qwen3.6-35B-A3B-MTP-GGUF", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use havenoammo/Qwen3.6-35B-A3B-MTP-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "havenoammo/Qwen3.6-35B-A3B-MTP-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "havenoammo/Qwen3.6-35B-A3B-MTP-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/havenoammo/Qwen3.6-35B-A3B-MTP-GGUF
- SGLang
How to use havenoammo/Qwen3.6-35B-A3B-MTP-GGUF with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "havenoammo/Qwen3.6-35B-A3B-MTP-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "havenoammo/Qwen3.6-35B-A3B-MTP-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "havenoammo/Qwen3.6-35B-A3B-MTP-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "havenoammo/Qwen3.6-35B-A3B-MTP-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Unsloth Studio
How to use havenoammo/Qwen3.6-35B-A3B-MTP-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 havenoammo/Qwen3.6-35B-A3B-MTP-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 havenoammo/Qwen3.6-35B-A3B-MTP-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for havenoammo/Qwen3.6-35B-A3B-MTP-GGUF to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="havenoammo/Qwen3.6-35B-A3B-MTP-GGUF", max_seq_length=2048, ) - Docker Model Runner
How to use havenoammo/Qwen3.6-35B-A3B-MTP-GGUF with Docker Model Runner:
docker model run hf.co/havenoammo/Qwen3.6-35B-A3B-MTP-GGUF
Is it possible to only download the mtp gguf (<1GB one) to use with existing ggufs?
Or do I need to download the whole new gguf with mtp inside
Sure! You can download just the MTP gguf from https://huggingface.co/havenoammo/Qwen3.6-35B-A3B-MTP-GGUF/resolve/main/35BA3B-MTP.gguf and the convert.py script from https://huggingface.co/havenoammo/Qwen3.6-35B-A3B-MTP-GGUF/resolve/main/convert.py, then graft the MTP layers onto your existing model by following this recipe:
# Create and activate a virtual environment
uv venv .venv --seed
source .venv/bin/activate
# Install the gguf library
uv pip install gguf
# Run the grafting script: convert.py <base model> <MTP source> <output>
python convert.py Qwen3.6-27B-UD-Q4_K_XL.gguf MTP-Q8_0.gguf Qwen3.6-27B-MTP-UD-Q4_K_XL.gguf
Sure! You can download just the MTP gguf from https://huggingface.co/havenoammo/Qwen3.6-35B-A3B-MTP-GGUF/resolve/main/35BA3B-MTP.gguf and the convert.py script from https://huggingface.co/havenoammo/Qwen3.6-35B-A3B-MTP-GGUF/resolve/main/convert.py, then graft the MTP layers onto your existing model by following this recipe:
# Create and activate a virtual environment uv venv .venv --seed source .venv/bin/activate # Install the gguf library uv pip install gguf # Run the grafting script: convert.py <base model> <MTP source> <output> python convert.py Qwen3.6-27B-UD-Q4_K_XL.gguf MTP-Q8_0.gguf Qwen3.6-27B-MTP-UD-Q4_K_XL.gguf
Thanks!
So if i have a IQ4_NL from UD, i can still patch it with MTP-Q8_0.gguf??
So if i have a IQ4_NL from UD, i can still patch it with MTP-Q8_0.gguf??
Yes, that's right.