Instructions to use nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx") 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 AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx") model = AutoModelForMultimodalLM.from_pretrained("nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx", device_map="auto") 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?"} ] }, ] inputs = processor.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - MLX
How to use nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx") config = load_config("nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- vLLM
How to use nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx", "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/nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx
- SGLang
How to use nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx 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 "nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx" \ --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": "nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx", "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 "nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx" \ --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": "nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx", "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 nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx 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 nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx 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 nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx", max_seq_length=2048, ) - Pi
How to use nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx"
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 nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx
Run Hermes
hermes
- OpenClaw new
How to use nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx"
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 "nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx" \ --custom-provider-id mlx-lm \ --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 nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx with Docker Model Runner:
docker model run hf.co/nightmedia/Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx
633d014 81aa96d 633d014 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 | {# Define the macros for XML conversion #}
{%- macro render_item_list(item_list, tag_name='required') -%}
{%- if item_list is defined and item_list is iterable and item_list | length > 0 -%}
<{{ tag_name }}>[{{- item_list | join(", ") -}}]</{{ tag_name }}>
{%- endif -%}
{%- endmacro -%}
{%- macro render_extra_keys(json_dict, handled_keys) -%}
{%- if json_dict is mapping -%}
{%- for json_key in json_dict if json_key not in handled_keys -%}
<{{ json_key }}>{{ json_dict[json_key] }}</{{ json_key }}>
{%- endfor -%}
{%- endif -%}
{%- endmacro -%}
{%- set image_count = namespace(value=0) %}
{%- set video_count = namespace(value=0) %}
{%- set add_vision_id = add_vision_id if add_vision_id is defined else true %}
{# Set Instruct mode here #}
{%- set _enable_thinking = false %}
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
{%- if content is string %}
{{- content }}
{%- elif content is iterable and content is not mapping %}
{%- for item in content %}
{%- if 'image' in item or 'image_url' in item or (item is mapping and item.get('type') == 'image') %}
{%- if is_system_content %}
{{- raise_exception('System message cannot contain images.') }}
{%- endif %}
{%- if do_vision_count %}
{%- set image_count.value = image_count.value + 1 %}
{%- endif %}
{%- if add_vision_id %}
{{- 'Picture ' ~ image_count.value ~ ': ' }}
{%- endif %}
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
{%- elif 'video' in item or (item is mapping and item.get('type') == 'video') %}
{%- if is_system_content %}
{{- raise_exception('System message cannot contain videos.') }}
{%- endif %}
{%- if do_vision_count %}
{%- set video_count.value = video_count.value + 1 %}
{%- endif %}
{%- if add_vision_id %}
{{- 'Video ' ~ video_count.value ~ ': ' }}
{%- endif %}
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
{%- elif item is mapping and 'text' in item %}
{{- item.text }}
{%- else %}
{{- raise_exception('Unexpected item type in content.') }}
{%- endif %}
{%- endfor %}
{%- elif content is none or content is undefined %}
{{- '' }}
{%- else %}
{{- raise_exception('Unexpected content type.') }}
{%- endif %}
{%- endmacro %}
{%- if not messages %}
{{- raise_exception('No messages provided.') }}
{%- endif %}
{# Flag to prevent double-rendering system prompt #}
{%- set ns = namespace(system_rendered=false) %}
{%- if tools and tools is iterable and tools is not mapping %}
{{- '<|im_start|>system\n# Tools\n\nYou have access to the following functions:\n\n<tools>' -}}
{%- for tool in tools -%}
{%- set function = tool.function -%}
{{- "\n<tool>\n<name>" + function.name + "</name>\n<description>" + function.description + "</description>" -}}
{%- if function.parameters and function.parameters.properties -%}
{%- for param_name, param_details in function.parameters.properties.items() -%}
{{- "\n<parameter>\n<name>" + param_name + "</name>\n<type>" + param_details.type + "</type>\n<description>" + (param_details.description | default('')) + "</description>" -}}
{{- render_item_list(function.parameters.required) -}}
{{- render_extra_keys(param_details, ['type', 'description']) -}}
{{- "\n</parameter>" -}}
{%- endfor -%}
{%- endif -%}
{{- "\n</tool>" -}}
{%- endfor -%}
{{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
{%- if messages[0].role == 'system' %}
{%- set content = render_content(messages[0].content, false, true)|trim %}
{%- if content %}
{{- '\n\n' + content }}
{%- endif %}
{%- set ns.system_rendered = true %}
{%- endif %}
{{- '<|im_end|>\n' }}
{%- else %}
{%- if messages[0].role == 'system' %}
{%- set content = render_content(messages[0].content, false, true)|trim %}
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
{%- set ns.system_rendered = true %}
{%- endif %}
{%- endif %}
{# Main Message Loop #}
{%- for message in messages %}
{%- if message.role == "system" and ns.system_rendered and loop.first %}
{%- continue %}
{%- endif %}
{%- set content = render_content(message.content, true)|trim %}
{%- if message.role == "system" %}
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
{%- elif message.role == "user" %}
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>\n' }}
{%- elif message.role == "assistant" %}
{%- set reasoning_content = '' %}
{%- if message.reasoning_content is defined and message.reasoning_content is string %}
{%- set reasoning_content = message.reasoning_content | trim %}
{%- elif '<think>' in content and '</think>' in content %}
{%- set reasoning_content = content.split('</think>')[0].split('<think>')[-1] | trim %}
{%- set content = content.split('</think>')[-1] | trim %}
{%- endif %}
{{- '<|im_start|>' + message.role + '\n' }}
{%- if reasoning_content %}
{{- '<think>\n' + reasoning_content + '\n</think>\n\n' }}
{%- endif %}
{{- content }}
{# Tool call formatting #}
{%- if message.tool_calls %}
{%- for tool_call in message.tool_calls %}
{%- set tc = tool_call.function if tool_call.function is defined else tool_call %}
{%- if loop.first and content %}{{- '\n\n' }}{%- elif not loop.first %}{{- '\n' }}{%- endif %}
{{- '<tool_call>\n<function=' + tc.name + '>\n' }}
{%- for args_name, args_value in tc.arguments|items %}
{{- '<parameter=' + args_name + '>\n' }}
{{- (args_value | tojson | safe if args_value is mapping or args_value is sequence else args_value | string) + '\n</parameter>\n' }}
{%- endfor %}
{{- '</function>\n</tool_call>' }}
{%- endfor %}
{%- endif %}
{{- '<|im_end|>\n' }}
{%- elif message.role == "tool" %}
{%- if loop.previtem and loop.previtem.role != "tool" %}{{- '<|im_start|>user' }}{%- endif %}
{{- '\n<tool_response>\n' + content + '\n</tool_response>' }}
{%- if loop.last or (loop.nextitem and loop.nextitem.role != "tool") %}{{- '<|im_end|>\n' }}{%- endif %}
{%- endif %}
{%- endfor %}
{# Final Generation Prompt #}
{%- if add_generation_prompt %}
{{- '<|im_start|>assistant\n' }}
{%- if enable_thinking is defined and enable_thinking is false %}
{{- '<think>\n\n</think>\n\n' }}
{%- else %}
{{- '<think>\n' }}
{%- endif %}
{%- endif %}
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