Instructions to use Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-GGUF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-GGUF") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-GGUF", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-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": "Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-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/Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-GGUF
- SGLang
How to use Jackrong/Qwopus3.6-35B-A3B-Coder-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 "Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-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 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 "Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-GGUF" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-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" } } ] } ] }' - Unsloth Studio
How to use Jackrong/Qwopus3.6-35B-A3B-Coder-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 Jackrong/Qwopus3.6-35B-A3B-Coder-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 Jackrong/Qwopus3.6-35B-A3B-Coder-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 Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-GGUF to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-GGUF", max_seq_length=2048, ) - Docker Model Runner
How to use Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-GGUF with Docker Model Runner:
docker model run hf.co/Jackrong/Qwopus3.6-35B-A3B-Coder-MTP-GGUF
Sampling
Big Thanks for the model!
Which sampling parameters do you recommend?
+1
I am currently using the following
llama-server \
-m ~/Projects/AI/models/Qwopus3.6-35B-A3B-Coder-MTP-Q4_K_M.gguf \
-ngl 20 -c 262144 -fa on -np 1 \
--spec-type draft-mtp --spec-draft-n-max 6 \
--top-p 0.95 \
--top-k 20 \
--min-p 0 \
--temp 0.6 \
--reasoning off
Really not sure if those are the right settings though, because I have just not had good experiences when Qwen 3.6 in general, seems too dumb to use Three.js correctly to make a Minecraft clone, at least it's not getting in loops as much. Maybe I'm not jamming it with enough MCPs and it's a Opencode issue, who knows, would like advise here Gemma has generally given me better results but everyone seems to disagree hopefully I'm just doing something wrong
Honestly getting way better results with just base Qwen, not where I expect though, I will give credit where credit is do much more eager to use tools than base Qwen though
Sorry for the very late reply.
You can generally use the official recommended sampling settings for Qwen3.6 with this model, as I did not make many changes to the sampling behavior.
In my experience, temp=0.6–1.0 and top_p=0.95 are both good choices. LM Studio usually defaults to around temp=1.0 and top_p=0.95, which gives the model more diversity in its responses.