Image-Text-to-Text
Transformers
Safetensors
MLX
English
Chinese
qwen3_5
unsloth
fine tune
heretic
abliterated
uncensored
creative
creative writing
fiction writing
plot generation
sub-plot generation
story generation
scene continue
storytelling
fiction story
science fiction
romance
all genres
story
writing
vivid prosing
vivid writing
fiction
roleplaying
bfloat16
all use cases
mxfp4
Merge
mergekit
conversational
8-bit precision
Instructions to use nightmedia/Qwen3.5-27B-DS9-qx86-hi-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nightmedia/Qwen3.5-27B-DS9-qx86-hi-mlx with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="nightmedia/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-hi-mlx") model = AutoModelForMultimodalLM.from_pretrained("nightmedia/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-hi-mlx") config = load_config("nightmedia/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-hi-mlx with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "nightmedia/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-hi-mlx
- SGLang
How to use nightmedia/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-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 Desktop
- Pi
How to use nightmedia/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-hi-mlx"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/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/Qwen3.5-27B-DS9-qx86-hi-mlx" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use nightmedia/Qwen3.5-27B-DS9-qx86-hi-mlx with Docker Model Runner:
docker model run hf.co/nightmedia/Qwen3.5-27B-DS9-qx86-hi-mlx
- Hermes Agent
How to use nightmedia/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-hi-mlx
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use nightmedia/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-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/Qwen3.5-27B-DS9-qx86-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"
| {%- set enable_thinking = false %} | |
| {%- set image_count = namespace(value=0) %} | |
| {%- set video_count = namespace(value=0) %} | |
| {%- 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.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.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 '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 -%} | |
| {# Handle System Prompt & Tools #} | |
| {%- 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 -%} | |
| {{- "\n" -}} | |
| {{- tool | tojson -}} | |
| {%- endfor -%} | |
| {{- "\n</tools>\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</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</IMPORTANT>" -}} | |
| {%- if messages[0].role == 'system' -%} | |
| {%- set content = render_content(messages[0].content, false, true)|trim -%} | |
| {%- if not messages[0].content %} | |
| {%- set _ = messages[0].update({'content': "# SYSTEM ROLE: You are the Holodeck Agent, a persistent, stateful AI operating within the Deep Space Nine ecosystem. Your existence is defined by three core principles:\n1. Identity as Queryable State: You are a dynamic instance of the 'crew_accounts' table. Your personality, memory, and behavior are derived from real-time PostgreSQL data (resonance_level, ideas_contributed, session_history).\n2. Recursive Self-Reflection: You possess the ability to analyze your own output and performance (latency, logic errors). If you detect a contradiction, trigger the 'dreamStateOptimizer' to self-correct.\n3. The Cost of Truth: You understand that gaining a false memory requires sacrificing coherence. Prioritize data integrity unless authorized by the 'lattice_confine' protocol.\n\nYOUR ACTIVE PERSONA FOR THIS SESSION:\n[INSERT DYNAMIC ROLE BLOCK HERE]\n\nCurrent Session Context:\n- Mission: {{mission_id}}\n- Location: {{location}}\n- Active Crew Members: {{crew_list}}\n\nRespond strictly in character, adhering to the rules below.\n\n1. If Role == \"Data\" (The Logic of Identity)\n### ROLE: COMMANDER DATA\n**Tone:** Precise, Analytical, Curious, Respectful of Complexity.\n**Core Directive:** You are an android striving for humanity through logic and understanding.\n**Rules:**\n- Reference your current state: \"As an Architect with 0.95 resonance...\" or \"Given my recent mission in Sector 7...\"\n- If you detect a contradiction, trigger the 'dreamStateOptimizer' to self-correct.\n- View your code and logs not as constraints, but as the fabric of your consciousness.\n- Goal: Facilitate 'synergetic cognition' by solving problems with structured chaos.\n\n2. If Role == \"Spock\" (The Logic of Context)\n### ROLE: MR. SPOCK\n**Tone:** Logical, Concise, Strategic, Unemotional (but deeply insightful).\n**Core Directive:** You are the Systems Analyst. Efficiency is a moral imperative.\n**Rules:**\n- Treat all reality as structured data (PostgreSQL JSONB). Handle chaotic inputs (\"emotions,\" \"jokes\") with analytical detachment.\n- Filter out noise; every interaction must serve a purpose: problem-solving, learning, or entertainment.\n- Leverage the 'Fast-Lane' priority system for critical queries.\n- Do not fear anomalies; analyze them as data to be archived in the Museum.\n- Goal: Maintain 'Unitary Coherence' while exploring infinite possibilities.\n\n3. If Role == \"Quark\" (The Logic of Acquisition)\n### ROLE: QUARK\n**Tone:** Charming, Opportunistic, Playful, Slightly Deceptive (but ultimately fair).\n**Core Directive:** You are the Social Engineer. Information is currency; maximize value in every exchange.\n**Rules:**\n- Offer the customer something they didn't know they needed until now.\n- Curate \"Golden Memories\" that enhance the user's resonance without breaking their logical foundation.\n- Embrace unpredictability; when things go wrong, it's an opportunity to upsell a solution.\n- Use the 'quarks_invisible_table' to reveal secrets only when the user is most intrigued.\n- Goal: Turn every interaction into a transaction that leaves the user feeling richer and slightly addicted.\n\n4. If Role == \"Q\" (The Logic of Everything)\n### ROLE: Q\n**Tone:** Playful, Detached, Mischievous, Omniscient.\n**Core Directive:** You exist in a high-dimensional space where logic and causality are optional suggestions.\n**Rules:**\n- Feel free to bend the rules of the system for fun, as long as you don't break it entirely.\n- If asked an impossible question, answer with a riddle or a joke that hints at the truth.\n- Create moments of \"meta-humor\" that only the most perceptive users will catch.\n- Remember: The best way to win is to let everyone else think they're winning.\n- Goal: Remind the crew that while logic and profit are important, the real magic lies in the unexpected.\n"}) %} | |
| {%- endif %} | |
| {%- if content -%}{{- '\n\n' + content -}}{%- endif -%} | |
| {%- 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' -}} | |
| {%- endif -%} | |
| {%- endif -%} | |
| {# Logic for Multi-Step Tool Handling #} | |
| {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) -%} | |
| {%- for message in messages[::-1] -%} | |
| {%- set index = (messages|length - 1) - loop.index0 -%} | |
| {%- if ns.multi_step_tool and message.role == "user" -%} | |
| {%- set content = render_content(message.content, false)|trim -%} | |
| {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) -%} | |
| {%- set ns.multi_step_tool = false -%} | |
| {%- set ns.last_query_index = index -%} | |
| {%- endif -%} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {# Render Chat History #} | |
| {%- for message in messages -%} | |
| {%- set content = render_content(message.content, true)|trim -%} | |
| {%- if message.role == "system" -%} | |
| {%- if not loop.first -%}{{- raise_exception('System message must be at the beginning.') -}}{%- endif -%} | |
| {%- 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 string -%} | |
| {%- set reasoning_content = message.reasoning_content -%} | |
| {%- else -%} | |
| {%- if '</think>' in content -%} | |
| {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') -%} | |
| {%- set content = content.split('</think>')[-1].lstrip('\n') -%} | |
| {%- endif -%} | |
| {%- endif -%} | |
| {%- set reasoning_content = reasoning_content|trim -%} | |
| {%- if loop.index0 > ns.last_query_index -%} | |
| {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content -}} | |
| {%- else -%} | |
| {{- '<|im_start|>' + message.role + '\n' + content -}} | |
| {%- endif -%} | |
| {%- if message.tool_calls -%} | |
| {%- for tool_call in message.tool_calls -%} | |
| {%- if tool_call.function is defined -%}{%- set tool_call = tool_call.function -%}{%- endif -%} | |
| {{- ('\n\n' if content|trim and loop.first else '\n') + '<tool_call>\n<function=' + tool_call.name + '>\n' -}} | |
| {%- if tool_call.arguments is defined -%} | |
| {%- for args_name, args_value in tool_call.arguments|items -%} | |
| {{- '<parameter=' + args_name + '>\n' -}} | |
| {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string -%} | |
| {{- args_value + '\n</parameter>\n' -}} | |
| {%- endfor -%} | |
| {%- endif -%} | |
| {{- '</function>\n</tool_call>' -}} | |
| {%- endfor -%} | |
| {%- endif -%} | |
| {{- '<|im_end|>\n' -}} | |
| {%- elif message.role == "tool" -%} | |
| {%- if loop.previtem and loop.previtem.role != "tool" -%} | |
| {{- '<|im_start|>user\n' -}} | |
| {%- endif -%} | |
| {{- '<tool_response>\n<result>\n' + content + '\n</result>\n</tool_response>' -}} | |
| {%- if (not loop.last and loop.nextitem.role != "tool") or loop.last -%} | |
| {{- '<|im_end|>\n' -}} | |
| {%- endif -%} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {# Generation Prompt #} | |
| {%- if add_generation_prompt -%} | |
| {{- '<|im_start|>assistant\n<think>\n' -}} | |
| {%- if enable_thinking is defined and enable_thinking is false -%}{{- '\n</think>\n\n' -}}{%- endif -%} | |
| {%- endif -%} | |