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
Add files using upload-large-folder tool
Browse files- .gitattributes +1 -0
- README.md +16 -107
- chat_template.jinja +164 -0
- config.json +0 -0
- generation_config.json +13 -0
- model-00001-of-00004.safetensors +3 -0
- model-00002-of-00004.safetensors +3 -0
- model-00003-of-00004.safetensors +3 -0
- model-00004-of-00004.safetensors +3 -0
- model.safetensors.index.json +0 -0
- preprocessor_config.json +21 -0
- processor_config.json +50 -0
- tokenizer.json +3 -0
- tokenizer_config.json +34 -0
- video_preprocessor_config.json +21 -0
- vocab.json +0 -0
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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---
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base_model:
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- Qwen/Qwen3.6-27B
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- DavidAU/Qwen3.5-27B-Claude-4.6-OS-INSTRUCT
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- DavidAU/Qwen3.6-27B-Heretic2-Uncensored-Finetune-Thinking
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- nightmedia/Qwen3.6-27B-Architect-Polaris
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- armand0e/Qwen3.6-27B-Fable-5-Experimental
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language:
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- en
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- zh
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- ja
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- es
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pipeline_tag: image-text-to-text
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library_name: transformers
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tags:
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- transformers
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- coding
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- research
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- unsloth
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- qwen3_5
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- qwen3_6
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- qwen
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- fable
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- qwen3.6
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- qwen3.5
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- claude4.6
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- claude-distillation
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- distillation
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- polaris
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- polaris-alpha
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- reasoning
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- chain-of-thought
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- long-cot
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- sft
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- lora
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- 1M context
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- 256k context
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- Qwen3.6
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- All use cases
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- instruction-tuned
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- conversational
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- text-generation
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- multilingual
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- math
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- stem
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- coding
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- research
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- experimental
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- Deckard(qx)
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- creative
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- creative writing
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- fiction writing
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- plot generation
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- sub-plot generation
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- fiction writing
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- story generation
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- scene continue
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- storytelling
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- fiction story
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- science fiction
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- all genres
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- story
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- writing
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- vivid prosing
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- vivid writing
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- fiction
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- bf16
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- roleplaying
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- mergekit
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- merge
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- mlx
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---
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# Qwen3.6-27B-Architect-Polaris-Fable-qx64-hi-mlx
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This model is a NuSLERP merge of:
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- nightmedia/Qwen3.6-27B-Architect-Polaris
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- armand0e/Qwen3.6-27B-Fable-5-Experimental
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```brainwaves
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arc arc/e boolq hswag obkqa piqa wino
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qx86-hi 0.689,0.863,0.909
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qx64-hi ...coming soon
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```
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## Model components
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arc arc/e boolq hswag obkqa piqa wino
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mxfp8 0.709,0.874,0.909,0.788,0.494,0.820,0.768
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mxfp4 0.698,0.874,0.909,0.786,0.494,0.820,0.759
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```
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qx86-hi 0.650,0.813,0.909
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```
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models:
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- model: nightmedia/Qwen3.6-27B-Architect-Polaris
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parameters:
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weight: 1.6
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- model: armand0e/Qwen3.6-27B-Fable-5-Experimental
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parameters:
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weight: 0.4
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merge_method: nuslerp
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dtype: bfloat16
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name: Qwen3.6-27B-Architect-Polaris-Fable
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```
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---
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{}
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---
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# Qwen3.6-27B-Architect-Polaris-Fable-XML-Instruct-qx64-hi-mlx
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## Use with mlx
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```bash
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pip install mlx-lm
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```
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```python
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from mlx_lm import load, generate
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model, tokenizer = load("Qwen3.6-27B-Architect-Polaris-Fable-XML-Instruct-qx64-hi-mlx")
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prompt = "hello"
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if tokenizer.chat_template is not None:
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messages = [{"role": "user", "content": prompt}]
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prompt = tokenizer.apply_chat_template(
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messages, add_generation_prompt=True, return_dict=False,
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)
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response = generate(model, tokenizer, prompt=prompt, verbose=True)
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```
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|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{# Define the macros for XML conversion #}
|
| 2 |
+
{%- macro render_item_list(item_list, tag_name='required') -%}
|
| 3 |
+
{%- if item_list is defined and item_list is iterable and item_list | length > 0 -%}
|
| 4 |
+
<{{ tag_name }}>[{{- item_list | join(", ") -}}]</{{ tag_name }}>
|
| 5 |
+
{%- endif -%}
|
| 6 |
+
{%- endmacro -%}
|
| 7 |
+
|
| 8 |
+
{%- macro render_extra_keys(json_dict, handled_keys) -%}
|
| 9 |
+
{%- if json_dict is mapping -%}
|
| 10 |
+
{%- for json_key in json_dict if json_key not in handled_keys -%}
|
| 11 |
+
<{{ json_key }}>{{ json_dict[json_key] }}</{{ json_key }}>
|
| 12 |
+
{%- endfor -%}
|
| 13 |
+
{%- endif -%}
|
| 14 |
+
{%- endmacro -%}
|
| 15 |
+
|
| 16 |
+
|
| 17 |
+
{%- set image_count = namespace(value=0) %}
|
| 18 |
+
{%- set video_count = namespace(value=0) %}
|
| 19 |
+
{%- set add_vision_id = add_vision_id if add_vision_id is defined else true %}
|
| 20 |
+
|
| 21 |
+
{# Set Instruct mode here #}
|
| 22 |
+
|
| 23 |
+
{%- set enable_thinking = false %}
|
| 24 |
+
{%- macro render_content(content, do_vision_count, is_system_content=false) %}
|
| 25 |
+
{%- if content is string %}
|
| 26 |
+
{{- content }}
|
| 27 |
+
{%- elif content is iterable and content is not mapping %}
|
| 28 |
+
{%- for item in content %}
|
| 29 |
+
{%- if 'image' in item or 'image_url' in item or (item is mapping and item.get('type') == 'image') %}
|
| 30 |
+
{%- if is_system_content %}
|
| 31 |
+
{{- raise_exception('System message cannot contain images.') }}
|
| 32 |
+
{%- endif %}
|
| 33 |
+
{%- if do_vision_count %}
|
| 34 |
+
{%- set image_count.value = image_count.value + 1 %}
|
| 35 |
+
{%- endif %}
|
| 36 |
+
{%- if add_vision_id %}
|
| 37 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
|
| 38 |
+
{%- endif %}
|
| 39 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
|
| 40 |
+
{%- elif 'video' in item or (item is mapping and item.get('type') == 'video') %}
|
| 41 |
+
{%- if is_system_content %}
|
| 42 |
+
{{- raise_exception('System message cannot contain videos.') }}
|
| 43 |
+
{%- endif %}
|
| 44 |
+
{%- if do_vision_count %}
|
| 45 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 46 |
+
{%- endif %}
|
| 47 |
+
{%- if add_vision_id %}
|
| 48 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
|
| 49 |
+
{%- endif %}
|
| 50 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
|
| 51 |
+
{%- elif item is mapping and 'text' in item %}
|
| 52 |
+
{{- item.text }}
|
| 53 |
+
{%- else %}
|
| 54 |
+
{{- raise_exception('Unexpected item type in content.') }}
|
| 55 |
+
{%- endif %}
|
| 56 |
+
{%- endfor %}
|
| 57 |
+
{%- elif content is none or content is undefined %}
|
| 58 |
+
{{- '' }}
|
| 59 |
+
{%- else %}
|
| 60 |
+
{{- raise_exception('Unexpected content type.') }}
|
| 61 |
+
{%- endif %}
|
| 62 |
+
{%- endmacro %}
|
| 63 |
+
|
| 64 |
+
{%- if not messages %}
|
| 65 |
+
{{- raise_exception('No messages provided.') }}
|
| 66 |
+
{%- endif %}
|
| 67 |
+
|
| 68 |
+
{# Flag to prevent double-rendering system prompt #}
|
| 69 |
+
{%- set ns = namespace(system_rendered=false) %}
|
| 70 |
+
|
| 71 |
+
{%- if tools and tools is iterable and tools is not mapping %}
|
| 72 |
+
|
| 73 |
+
{{- '<|im_start|>system\n# Tools\n\nYou have access to the following functions:\n\n<tools>' -}}
|
| 74 |
+
{%- for tool in tools -%}
|
| 75 |
+
{%- set function = tool.function -%}
|
| 76 |
+
{{- "\n<tool>\n<name>" + function.name + "</name>\n<description>" + function.description + "</description>" -}}
|
| 77 |
+
{%- if function.parameters and function.parameters.properties -%}
|
| 78 |
+
{%- for param_name, param_details in function.parameters.properties.items() -%}
|
| 79 |
+
{{- "\n<parameter>\n<name>" + param_name + "</name>\n<type>" + param_details.type + "</type>\n<description>" + (param_details.description | default('')) + "</description>" -}}
|
| 80 |
+
{{- render_item_list(function.parameters.required) -}}
|
| 81 |
+
{{- render_extra_keys(param_details, ['type', 'description']) -}}
|
| 82 |
+
{{- "\n</parameter>" -}}
|
| 83 |
+
{%- endfor -%}
|
| 84 |
+
{%- endif -%}
|
| 85 |
+
{{- "\n</tool>" -}}
|
| 86 |
+
{%- endfor -%}
|
| 87 |
+
|
| 88 |
+
{{- '\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>' }}
|
| 89 |
+
|
| 90 |
+
{%- if messages[0].role == 'system' %}
|
| 91 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 92 |
+
{%- if content %}
|
| 93 |
+
{{- '\n\n' + content }}
|
| 94 |
+
{%- endif %}
|
| 95 |
+
{%- set ns.system_rendered = true %}
|
| 96 |
+
{%- endif %}
|
| 97 |
+
{{- '<|im_end|>\n' }}
|
| 98 |
+
{%- else %}
|
| 99 |
+
{%- if messages[0].role == 'system' %}
|
| 100 |
+
{%- set content = render_content(messages[0].content, false, true)|trim %}
|
| 101 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 102 |
+
{%- set ns.system_rendered = true %}
|
| 103 |
+
{%- endif %}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
|
| 106 |
+
{# Main Message Loop #}
|
| 107 |
+
{%- for message in messages %}
|
| 108 |
+
{%- if message.role == "system" and ns.system_rendered and loop.first %}
|
| 109 |
+
{%- continue %}
|
| 110 |
+
{%- endif %}
|
| 111 |
+
|
| 112 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 113 |
+
|
| 114 |
+
{%- if message.role == "system" %}
|
| 115 |
+
{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
|
| 116 |
+
{%- elif message.role == "user" %}
|
| 117 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>\n' }}
|
| 118 |
+
{%- elif message.role == "assistant" %}
|
| 119 |
+
{%- set reasoning_content = '' %}
|
| 120 |
+
{%- if message.reasoning_content is defined and message.reasoning_content is string %}
|
| 121 |
+
{%- set reasoning_content = message.reasoning_content | trim %}
|
| 122 |
+
{%- elif '<think>' in content and '</think>' in content %}
|
| 123 |
+
{%- set reasoning_content = content.split('</think>')[0].split('<think>')[-1] | trim %}
|
| 124 |
+
{%- set content = content.split('</think>')[-1] | trim %}
|
| 125 |
+
{%- endif %}
|
| 126 |
+
|
| 127 |
+
{{- '<|im_start|>' + message.role + '\n' }}
|
| 128 |
+
|
| 129 |
+
{%- if reasoning_content %}
|
| 130 |
+
{{- '<think>\n' + reasoning_content + '\n</think>\n\n' }}
|
| 131 |
+
{%- endif %}
|
| 132 |
+
|
| 133 |
+
{{- content }}
|
| 134 |
+
|
| 135 |
+
{# Tool call formatting #}
|
| 136 |
+
{%- if message.tool_calls %}
|
| 137 |
+
{%- for tool_call in message.tool_calls %}
|
| 138 |
+
{%- set tc = tool_call.function if tool_call.function is defined else tool_call %}
|
| 139 |
+
{%- if loop.first and content %}{{- '\n\n' }}{%- elif not loop.first %}{{- '\n' }}{%- endif %}
|
| 140 |
+
{{- '<tool_call>\n<function=' + tc.name + '>\n' }}
|
| 141 |
+
{%- for args_name, args_value in tc.arguments|items %}
|
| 142 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 143 |
+
{{- (args_value | tojson | safe if args_value is mapping or args_value is sequence else args_value | string) + '\n</parameter>\n' }}
|
| 144 |
+
{%- endfor %}
|
| 145 |
+
{{- '</function>\n</tool_call>' }}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- endif %}
|
| 148 |
+
{{- '<|im_end|>\n' }}
|
| 149 |
+
{%- elif message.role == "tool" %}
|
| 150 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}{{- '<|im_start|>user' }}{%- endif %}
|
| 151 |
+
{{- '\n<tool_response>\n' + content + '\n</tool_response>' }}
|
| 152 |
+
{%- if loop.last or (loop.nextitem and loop.nextitem.role != "tool") %}{{- '<|im_end|>\n' }}{%- endif %}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endfor %}
|
| 155 |
+
|
| 156 |
+
{# Final Generation Prompt #}
|
| 157 |
+
{%- if add_generation_prompt %}
|
| 158 |
+
{{- '<|im_start|>assistant\n' }}
|
| 159 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 160 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 161 |
+
{%- else %}
|
| 162 |
+
{{- '<think>\n' }}
|
| 163 |
+
{%- endif %}
|
| 164 |
+
{%- endif %}
|
|
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|
|
|
|
@@ -0,0 +1,13 @@
|
|
|
|
|
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"do_sample": true,
|
| 3 |
+
"eos_token_id": [
|
| 4 |
+
248046,
|
| 5 |
+
248046,
|
| 6 |
+
248044
|
| 7 |
+
],
|
| 8 |
+
"pad_token_id": 248044,
|
| 9 |
+
"temperature": 1.0,
|
| 10 |
+
"top_k": 20,
|
| 11 |
+
"top_p": 0.95,
|
| 12 |
+
"transformers_version": "5.12.1"
|
| 13 |
+
}
|
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:bd88679488e027cbb1fa1f1b5ee55953958a053f0d53ac5429c5a7d84d9b350f
|
| 3 |
+
size 5360241014
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|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:65ad04bb229ef0aa3ac2db3e4310316f170b0ee529f4401d01958b8e524b5014
|
| 3 |
+
size 5339530556
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|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6183c323df6badda1b24d97ef04c2ea3a394c6a2f20e3de82341e1c4f4845aba
|
| 3 |
+
size 5367688619
|
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:39e005db0e81d14afb1009c442546b81fe6ac73e423aaf869011bea919ce33a2
|
| 3 |
+
size 4878525056
|
|
The diff for this file is too large to render.
See raw diff
|
|
|
|
@@ -0,0 +1,21 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"size": {
|
| 3 |
+
"longest_edge": 16777216,
|
| 4 |
+
"shortest_edge": 65536
|
| 5 |
+
},
|
| 6 |
+
"patch_size": 16,
|
| 7 |
+
"temporal_patch_size": 2,
|
| 8 |
+
"merge_size": 2,
|
| 9 |
+
"image_mean": [
|
| 10 |
+
0.5,
|
| 11 |
+
0.5,
|
| 12 |
+
0.5
|
| 13 |
+
],
|
| 14 |
+
"image_std": [
|
| 15 |
+
0.5,
|
| 16 |
+
0.5,
|
| 17 |
+
0.5
|
| 18 |
+
],
|
| 19 |
+
"processor_class": "Qwen3VLProcessor",
|
| 20 |
+
"image_processor_type": "Qwen2VLImageProcessorFast"
|
| 21 |
+
}
|
|
@@ -0,0 +1,50 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"image_processor": {
|
| 3 |
+
"do_convert_rgb": true,
|
| 4 |
+
"do_normalize": true,
|
| 5 |
+
"do_rescale": true,
|
| 6 |
+
"image_mean": [
|
| 7 |
+
0.5,
|
| 8 |
+
0.5,
|
| 9 |
+
0.5
|
| 10 |
+
],
|
| 11 |
+
"image_processor_type": "Qwen3VLImageProcessor",
|
| 12 |
+
"image_std": [
|
| 13 |
+
0.5,
|
| 14 |
+
0.5,
|
| 15 |
+
0.5
|
| 16 |
+
],
|
| 17 |
+
"max_pixels": 16777216,
|
| 18 |
+
"merge_size": 2,
|
| 19 |
+
"min_pixels": 65536,
|
| 20 |
+
"patch_size": 16,
|
| 21 |
+
"rescale_factor": 0.00392156862745098,
|
| 22 |
+
"temporal_patch_size": 2
|
| 23 |
+
},
|
| 24 |
+
"processor_class": "Qwen3VLProcessor",
|
| 25 |
+
"video_processor": {
|
| 26 |
+
"do_convert_rgb": true,
|
| 27 |
+
"do_normalize": true,
|
| 28 |
+
"do_rescale": true,
|
| 29 |
+
"fps": 2.0,
|
| 30 |
+
"image_mean": [
|
| 31 |
+
0.5,
|
| 32 |
+
0.5,
|
| 33 |
+
0.5
|
| 34 |
+
],
|
| 35 |
+
"image_std": [
|
| 36 |
+
0.5,
|
| 37 |
+
0.5,
|
| 38 |
+
0.5
|
| 39 |
+
],
|
| 40 |
+
"max_frames": 768,
|
| 41 |
+
"max_pixels": 25165824,
|
| 42 |
+
"merge_size": 2,
|
| 43 |
+
"min_frames": 4,
|
| 44 |
+
"min_pixels": 4096,
|
| 45 |
+
"patch_size": 16,
|
| 46 |
+
"rescale_factor": 0.00392156862745098,
|
| 47 |
+
"temporal_patch_size": 2,
|
| 48 |
+
"video_processor_type": "Qwen3VLVideoProcessor"
|
| 49 |
+
}
|
| 50 |
+
}
|
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523
|
| 3 |
+
size 19989325
|
|
@@ -0,0 +1,34 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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| 1 |
+
{
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| 2 |
+
"add_prefix_space": false,
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| 3 |
+
"audio_bos_token": "<|audio_start|>",
|
| 4 |
+
"audio_eos_token": "<|audio_end|>",
|
| 5 |
+
"audio_token": "<|audio_pad|>",
|
| 6 |
+
"backend": "tokenizers",
|
| 7 |
+
"bos_token": null,
|
| 8 |
+
"clean_up_tokenization_spaces": false,
|
| 9 |
+
"eos_token": "<|im_end|>",
|
| 10 |
+
"errors": "replace",
|
| 11 |
+
"image_token": "<|image_pad|>",
|
| 12 |
+
"is_local": true,
|
| 13 |
+
"local_files_only": false,
|
| 14 |
+
"model_max_length": 262144,
|
| 15 |
+
"model_specific_special_tokens": {
|
| 16 |
+
"audio_bos_token": "<|audio_start|>",
|
| 17 |
+
"audio_eos_token": "<|audio_end|>",
|
| 18 |
+
"audio_token": "<|audio_pad|>",
|
| 19 |
+
"image_token": "<|image_pad|>",
|
| 20 |
+
"video_token": "<|video_pad|>",
|
| 21 |
+
"vision_bos_token": "<|vision_start|>",
|
| 22 |
+
"vision_eos_token": "<|vision_end|>"
|
| 23 |
+
},
|
| 24 |
+
"pad_token": "<|endoftext|>",
|
| 25 |
+
"padding_side": "right",
|
| 26 |
+
"pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
|
| 27 |
+
"processor_class": "Qwen3VLProcessor",
|
| 28 |
+
"split_special_tokens": false,
|
| 29 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 30 |
+
"unk_token": null,
|
| 31 |
+
"video_token": "<|video_pad|>",
|
| 32 |
+
"vision_bos_token": "<|vision_start|>",
|
| 33 |
+
"vision_eos_token": "<|vision_end|>"
|
| 34 |
+
}
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@@ -0,0 +1,21 @@
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| 1 |
+
{
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| 2 |
+
"size": {
|
| 3 |
+
"longest_edge": 25165824,
|
| 4 |
+
"shortest_edge": 4096
|
| 5 |
+
},
|
| 6 |
+
"patch_size": 16,
|
| 7 |
+
"temporal_patch_size": 2,
|
| 8 |
+
"merge_size": 2,
|
| 9 |
+
"image_mean": [
|
| 10 |
+
0.5,
|
| 11 |
+
0.5,
|
| 12 |
+
0.5
|
| 13 |
+
],
|
| 14 |
+
"image_std": [
|
| 15 |
+
0.5,
|
| 16 |
+
0.5,
|
| 17 |
+
0.5
|
| 18 |
+
],
|
| 19 |
+
"processor_class": "Qwen3VLProcessor",
|
| 20 |
+
"video_processor_type": "Qwen3VLVideoProcessor"
|
| 21 |
+
}
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