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Upload Qwen3.5-35B-A3B-RAM-12.5GB-MLX

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.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,79 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ library_name: mlx
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+ tags:
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+ - mlx
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+ - quantized
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+ - mixed-precision
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+ - qwen3.5
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+ - moe
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+ license: other
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+ license_name: polyform-noncommercial
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+ base_model: Qwen/Qwen3.5-35B-A3B
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+ base_model_relation: quantized
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+ pipeline_tag: text-generation
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+ ---
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+
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+ # Qwen3.5-35B-A3B — 12.5GB (MLX)
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+
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+ Mixed-precision quantized version of [Qwen/Qwen3.5-35B-A3B](https://huggingface.co/Qwen/Qwen3.5-35B-A3B) optimised by [baa.ai](https://baa.ai) using a proprietary Black Sheep AI method.
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+
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+ Per-tensor bit-width allocation via advanced sensitivity analysis and budget-constrained optimisation — no calibration data required.
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+
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+ ## Metrics
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+
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+ | Metric | Value |
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+ |--------|-------|
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+ | **Size on disk** | **12.54 GB** |
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+ | Average bits (LLM body) | 2.35 |
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+ | Bit distribution (LLM body) | 78% 2-bit, 18% 3-bit, 0% 4-bit, 2% 5-bit, 2% 6-bit, 1% 8-bit, 0% 16-bit |
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+ | Embeddings + lm_head | 4-bit |
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+ | WikiText-2 PPL (median, 256×2048, seed 42) | 7.355 |
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+ | WikiText-2 PPL (mean) | 7.308 |
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+
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+
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+ ## Usage
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+
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+ ```python
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+ from mlx_lm import load, generate
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+
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+ model, tokenizer = load("baa-ai/Qwen3.5-35B-A3B-RAM-12.5GB-MLX")
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+ response = generate(model, tokenizer, prompt="Hello!", max_tokens=256)
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+ print(response)
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+ ```
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+
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+ For chat applications, apply the chat template:
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+
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+ ```python
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+ prompt = tokenizer.apply_chat_template(
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+ [{"role": "user", "content": "Write a Python function that reverses a string."}],
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+ tokenize=False,
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+ add_generation_prompt=True,
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+ enable_thinking=False,
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+ )
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+ response = generate(model, tokenizer, prompt=prompt, max_tokens=2048)
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+ ```
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+
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+ ## Hardware
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+
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+ Apple Silicon Mac with **~16 GB** unified memory recommended for inference.
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+
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+ ## Variants
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+
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+ Other size points in this collection:
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+
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+ - [12 GB](https://huggingface.co/baa-ai/Qwen3.5-35B-A3B-RAM-12GB-MLX) · [13 GB](https://huggingface.co/baa-ai/Qwen3.5-35B-A3B-RAM-13GB-MLX) · [14 GB](https://huggingface.co/baa-ai/Qwen3.5-35B-A3B-RAM-14GB-MLX) · [15 GB](https://huggingface.co/baa-ai/Qwen3.5-35B-A3B-RAM-15GB-MLX)
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+ - [16 GB](https://huggingface.co/baa-ai/Qwen3.5-35B-A3B-RAM-16GB-MLX) · [17 GB](https://huggingface.co/baa-ai/Qwen3.5-35B-A3B-RAM-17GB-MLX) · [18 GB](https://huggingface.co/baa-ai/Qwen3.5-35B-A3B-RAM-18GB-MLX) · [19 GB](https://huggingface.co/baa-ai/Qwen3.5-35B-A3B-RAM-19GB-MLX) · [20 GB](https://huggingface.co/baa-ai/Qwen3.5-35B-A3B-RAM-20GB-MLX)
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+ - Larger: [25 GB](https://huggingface.co/baa-ai/Qwen3.5-35B-A3B-RAM-25GB-MLX) · [29 GB](https://huggingface.co/baa-ai/Qwen3.5-35B-A3B-RAM-29GB-MLX) · [31 GB](https://huggingface.co/baa-ai/Qwen3.5-35B-A3B-RAM-31GB-MLX)
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+
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+ ---
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+ *Quantized by [baa.ai](https://baa.ai)*
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+
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+ ---
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+
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+ ## Black Sheep AI Products
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+
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+ **[Shepherd](https://baa.ai/shepherd.html)** — Private AI deployment platform that shrinks frontier models by 50-60% through RAM compression, enabling enterprises to run sophisticated AI on single GPU instances or Apple Silicon hardware. Deploy in your VPC with zero data leaving your infrastructure. Includes CI/CD pipeline integration, fleet deployment across Apple Silicon clusters, air-gapped and sovereign deployment support, and multi-format export (MLX, GGUF). Annual cloud costs from ~$2,700 — or run on a Mac Studio for electricity only.
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+
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+ **[Watchman](https://baa.ai/watchman.html)** — Capability audit and governance platform for compressed AI models. Know exactly what your quantized model can do before it goes live. Watchman predicts which capabilities survive compression in minutes — replacing weeks of benchmarking. Includes compliance-ready reporting for regulated industries, quality valley warnings for counterproductive memory allocations, instant regression diagnosis tracing issues to specific tensors, and 22 adversarial security probes scanning for injection, leakage, hallucination, and code vulnerabilities.
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+
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+ Learn more at **[baa.ai](https://baa.ai)** — Sovereign AI.
chat_template.jinja ADDED
@@ -0,0 +1,154 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {%- set image_count = namespace(value=0) %}
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+ {%- set video_count = namespace(value=0) %}
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+ {%- macro render_content(content, do_vision_count, is_system_content=false) %}
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+ {%- if content is string %}
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+ {{- content }}
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+ {%- elif content is iterable and content is not mapping %}
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+ {%- for item in content %}
8
+ {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
9
+ {%- if is_system_content %}
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+ {{- raise_exception('System message cannot contain images.') }}
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+ {%- endif %}
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+ {%- if do_vision_count %}
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+ {%- set image_count.value = image_count.value + 1 %}
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+ {%- endif %}
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+ {%- if add_vision_id %}
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+ {{- 'Picture ' ~ image_count.value ~ ': ' }}
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+ {%- endif %}
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+ {{- '<|vision_start|><|image_pad|><|vision_end|>' }}
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+ {%- elif 'video' in item or item.type == 'video' %}
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+ {%- if is_system_content %}
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+ {{- raise_exception('System message cannot contain videos.') }}
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+ {%- endif %}
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+ {%- if do_vision_count %}
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+ {%- set video_count.value = video_count.value + 1 %}
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+ {%- endif %}
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+ {%- if add_vision_id %}
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+ {{- 'Video ' ~ video_count.value ~ ': ' }}
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+ {%- endif %}
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+ {{- '<|vision_start|><|video_pad|><|vision_end|>' }}
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+ {%- elif 'text' in item %}
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+ {{- item.text }}
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+ {%- else %}
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+ {{- raise_exception('Unexpected item type in content.') }}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- elif content is none or content is undefined %}
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+ {{- '' }}
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+ {%- else %}
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+ {{- raise_exception('Unexpected content type.') }}
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+ {%- endif %}
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+ {%- endmacro %}
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+ {%- if not messages %}
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+ {{- raise_exception('No messages provided.') }}
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+ {%- endif %}
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+ {%- if tools and tools is iterable and tools is not mapping %}
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+ {{- '<|im_start|>system\n' }}
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+ {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
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+ {%- for tool in tools %}
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+ {{- "\n" }}
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+ {{- tool | tojson }}
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+ {%- endfor %}
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+ {{- "\n</tools>" }}
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+ {{- '\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>' }}
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+ {%- if messages[0].role == 'system' %}
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+ {%- set content = render_content(messages[0].content, false, true)|trim %}
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+ {%- if content %}
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+ {{- '\n\n' + content }}
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+ {%- endif %}
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+ {%- endif %}
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+ {{- '<|im_end|>\n' }}
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+ {%- else %}
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+ {%- if messages[0].role == 'system' %}
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+ {%- set content = render_content(messages[0].content, false, true)|trim %}
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+ {{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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+ {%- for message in messages[::-1] %}
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+ {%- set index = (messages|length - 1) - loop.index0 %}
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+ {%- if ns.multi_step_tool and message.role == "user" %}
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+ {%- set content = render_content(message.content, false)|trim %}
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+ {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
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+ {%- set ns.multi_step_tool = false %}
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+ {%- set ns.last_query_index = index %}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- if ns.multi_step_tool %}
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+ {{- raise_exception('No user query found in messages.') }}
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+ {%- endif %}
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+ {%- for message in messages %}
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+ {%- set content = render_content(message.content, true)|trim %}
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+ {%- if message.role == "system" %}
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+ {%- if not loop.first %}
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+ {{- raise_exception('System message must be at the beginning.') }}
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+ {%- endif %}
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+ {%- elif message.role == "user" %}
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+ {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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+ {%- elif message.role == "assistant" %}
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+ {%- set reasoning_content = '' %}
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+ {%- if message.reasoning_content is string %}
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+ {%- set reasoning_content = message.reasoning_content %}
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+ {%- else %}
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+ {%- if '</think>' in content %}
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+ {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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+ {%- set content = content.split('</think>')[-1].lstrip('\n') %}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- set reasoning_content = reasoning_content|trim %}
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+ {%- if loop.index0 > ns.last_query_index %}
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+ {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
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+ {%- else %}
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+ {{- '<|im_start|>' + message.role + '\n' + content }}
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+ {%- endif %}
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+ {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
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+ {%- for tool_call in message.tool_calls %}
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+ {%- if tool_call.function is defined %}
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+ {%- set tool_call = tool_call.function %}
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+ {%- endif %}
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+ {%- if loop.first %}
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+ {%- if content|trim %}
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+ {{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
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+ {%- else %}
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+ {{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
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+ {%- endif %}
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+ {%- else %}
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+ {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
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+ {%- endif %}
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+ {%- if tool_call.arguments is defined %}
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+ {%- for args_name, args_value in tool_call.arguments|items %}
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+ {{- '<parameter=' + args_name + '>\n' }}
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+ {%- 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 %}
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+ {{- args_value }}
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+ {{- '\n</parameter>\n' }}
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+ {%- endfor %}
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+ {%- endif %}
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+ {{- '</function>\n</tool_call>' }}
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+ {%- endfor %}
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+ {%- endif %}
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+ {{- '<|im_end|>\n' }}
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+ {%- elif message.role == "tool" %}
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+ {%- if loop.previtem and loop.previtem.role != "tool" %}
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+ {{- '<|im_start|>user' }}
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+ {%- endif %}
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+ {{- '\n<tool_response>\n' }}
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+ {{- content }}
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+ {{- '\n</tool_response>' }}
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+ {%- if not loop.last and loop.nextitem.role != "tool" %}
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+ {{- '<|im_end|>\n' }}
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+ {%- elif loop.last %}
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+ {{- '<|im_end|>\n' }}
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+ {%- endif %}
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+ {%- else %}
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+ {{- raise_exception('Unexpected message role.') }}
145
+ {%- endif %}
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+ {%- endfor %}
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+ {%- if add_generation_prompt %}
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+ {{- '<|im_start|>assistant\n' }}
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+ {%- if enable_thinking is defined and enable_thinking is false %}
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+ {{- '<think>\n\n</think>\n\n' }}
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+ {%- else %}
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+ {{- '<think>\n' }}
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+ {%- endif %}
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+ {%- endif %}
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+ "add_prefix_space": false,
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+ "audio_bos_token": "<|audio_start|>",
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+ "audio_eos_token": "<|audio_end|>",
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+ "audio_token": "<|audio_pad|>",
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+ "backend": "tokenizers",
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+ "bos_token": null,
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+ "clean_up_tokenization_spaces": false,
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+ "eos_token": "<|im_end|>",
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+ "errors": "replace",
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+ "image_token": "<|image_pad|>",
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+ "is_local": true,
13
+ "local_files_only": false,
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+ "model_max_length": 262144,
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+ "model_specific_special_tokens": {
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+ "audio_bos_token": "<|audio_start|>",
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+ "audio_eos_token": "<|audio_end|>",
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+ "audio_token": "<|audio_pad|>",
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+ "image_token": "<|image_pad|>",
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+ "video_token": "<|video_pad|>",
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+ "vision_bos_token": "<|vision_start|>",
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+ "vision_eos_token": "<|vision_end|>"
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+ },
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+ "pad_token": "<|endoftext|>",
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+ "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+",
26
+ "split_special_tokens": false,
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+ "tokenizer_class": "Qwen2Tokenizer",
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+ "tool_parser_type": "qwen3_coder",
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+ "vision_bos_token": "<|vision_start|>",
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+ }