Text Generation
MLX
Safetensors
qwen3_5_moe
quantized
expert-pruning
reap
Mixture of Experts
optiq
apple-silicon
conversational
4-bit precision
Instructions to use mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B"
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": "mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B 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 "mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B"
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 mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B"
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 "mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B" \ --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"
OptiQ REAP: 128 of 256 experts retained
Browse files- .gitattributes +1 -0
- README.md +82 -0
- chat_template.jinja +154 -0
- config.json +0 -0
- generation_config.json +12 -0
- model-00001-of-00003.safetensors +3 -0
- model-00002-of-00003.safetensors +3 -0
- model-00003-of-00003.safetensors +3 -0
- model.safetensors.index.json +0 -0
- optiq_metadata.json +0 -0
- tokenizer.json +3 -0
- tokenizer_config.json +33 -0
.gitattributes
CHANGED
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@@ -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
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README.md
ADDED
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@@ -0,0 +1,82 @@
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---
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+
library_name: mlx
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license: apache-2.0
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pipeline_tag: text-generation
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base_model: mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit
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tags:
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- mlx
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- quantized
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- expert-pruning
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- reap
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- moe
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- optiq
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- apple-silicon
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- text-generation
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---
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# mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B
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> **Built with [mlx-optiq](https://mlx-optiq.com)**, the MLX-native toolkit to quantize, prune, fine-tune, and serve LLMs locally on Apple Silicon. [All OptiQ models](https://mlx-optiq.com/models) · [Docs](https://mlx-optiq.com/docs/)
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**11.4 GB instead of 20.4 GB. 14.4 GB of memory to run.**
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| | Parent | This model | |
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|---|---|---|---|
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| On disk | 20.4 GB | **11.4 GB** | −44% |
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| Peak memory | — | **14.4 GB** | |
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| Parameters | 34.7B | **18.3B** | −47% |
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| Decode | — | **—** | |
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| Capability Score | — | **—** | — |
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50% of the routed experts are removed from [mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit](https://huggingface.co/mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit); active parameters per token are unchanged, since top-8 routing is preserved and only the stored expert bank shrinks. That is why it gets smaller without getting slower.
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Retained experts are copied bit-for-bit from the parent quant. Nothing is dequantized, re-quantized, merged, or retrained.
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## What pruning costs
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| Benchmark | Parent | This model | Δ |
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|---|---|---|---|
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| MMLU | — | — | — |
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| GSM8K | — | — | — |
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| IFEval | — | — | — |
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| BFCL-V3 | — | — | — |
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| HumanEval | — | — | — |
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| HashHop | — | — | — |
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| **Capability Score** | **—** | **—** | **—** |
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**This variant was not separately benchmarked.** It is published under the recipe validated end to end on [Qwen3.6-35B-A3B-OptiQ-4bit-REAP-19B](https://huggingface.co/mlx-community/Qwen3.6-35B-A3B-OptiQ-4bit-REAP-19B), the same architecture at the same 50 % retention: Capability Score 80.03 -> 76.57, with the loss concentrated in MMLU (-21.4) and procedural ability intact (GSM8K +2.6, IFEval +4.3, BFCL -1.0, HumanEval -1.3).
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Two things *were* measured on this checkpoint. The ranking rule was chosen by scoring both candidates against the unpruned model, which picked the conditional mean. And the resulting divergence from the unpruned parent is **KL 0.213** — for reference, the checkpoints that degrade visibly under pruning measure above 1.0, and this one is well inside the range where generation is indistinguishable in review.
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## Details
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| Property | Value |
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|---|---|
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| Experts retained | 128 of 256 per layer |
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| Active experts per token | 8 (unchanged) |
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| Allocation | uniform (128 of 256 in every layer) |
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| Size | 11.4 GB (parent 20.4 GB) |
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| Parameters | 18.3B (parent 34.7B) |
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| Selection | REAP — mean of router weight x expert output norm, over the tokens each expert served |
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| Calibration | optiq six-domain mix, 8 samples |
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| MTP sidecar | absent |
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## Use it
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```bash
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pip install mlx-optiq
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optiq serve --model mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B
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```
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```python
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from mlx_lm import load, generate
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model, tok = load("mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit-REAP-18B")
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print(generate(model, tok, prompt="Hello", max_tokens=64))
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```
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## Method
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Expert pruning follows **REAP** (Cerebras Research, ICLR 2026 — [*REAP the Experts: Why Pruning Prevails for One-Shot MoE Compression*](https://arxiv.org/abs/2510.13999)). Experts are ranked by the conditional mean of router weight × expert output norm over calibration data; the lowest-ranked are removed and the router is sliced to match.
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OptiQ applies it **in the quantized domain** — directly on a quantized checkpoint, with no BF16 parent and no dequantization of survivors — via `optiq prune-experts`. See the [pruning docs](https://mlx-optiq.com/docs/prune).
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|
chat_template.jinja
ADDED
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@@ -0,0 +1,154 @@
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{%- set image_count = namespace(value=0) %}
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| 2 |
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{%- set video_count = namespace(value=0) %}
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| 3 |
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{%- macro render_content(content, do_vision_count, is_system_content=false) %}
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| 4 |
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{%- if content is string %}
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{{- content }}
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| 6 |
+
{%- elif content is iterable and content is not mapping %}
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| 7 |
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{%- for item in content %}
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| 8 |
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{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
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| 9 |
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{%- if is_system_content %}
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| 10 |
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{{- raise_exception('System message cannot contain images.') }}
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| 11 |
+
{%- endif %}
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| 12 |
+
{%- if do_vision_count %}
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| 13 |
+
{%- set image_count.value = image_count.value + 1 %}
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| 14 |
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{%- endif %}
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| 15 |
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{%- if add_vision_id %}
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| 16 |
+
{{- 'Picture ' ~ image_count.value ~ ': ' }}
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| 17 |
+
{%- endif %}
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| 18 |
+
{{- '<|vision_start|><|image_pad|><|vision_end|>' }}
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| 19 |
+
{%- elif 'video' in item or item.type == 'video' %}
|
| 20 |
+
{%- if is_system_content %}
|
| 21 |
+
{{- raise_exception('System message cannot contain videos.') }}
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| 22 |
+
{%- endif %}
|
| 23 |
+
{%- if do_vision_count %}
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| 24 |
+
{%- set video_count.value = video_count.value + 1 %}
|
| 25 |
+
{%- endif %}
|
| 26 |
+
{%- if add_vision_id %}
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| 27 |
+
{{- 'Video ' ~ video_count.value ~ ': ' }}
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| 28 |
+
{%- endif %}
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| 29 |
+
{{- '<|vision_start|><|video_pad|><|vision_end|>' }}
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| 30 |
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{%- elif 'text' in item %}
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| 31 |
+
{{- item.text }}
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| 32 |
+
{%- else %}
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| 33 |
+
{{- raise_exception('Unexpected item type in content.') }}
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| 34 |
+
{%- endif %}
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| 35 |
+
{%- endfor %}
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| 36 |
+
{%- elif content is none or content is undefined %}
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{{- '' }}
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| 38 |
+
{%- else %}
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| 39 |
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{{- raise_exception('Unexpected content type.') }}
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| 40 |
+
{%- endif %}
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| 41 |
+
{%- endmacro %}
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| 42 |
+
{%- if not messages %}
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| 43 |
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{{- raise_exception('No messages provided.') }}
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| 44 |
+
{%- endif %}
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| 45 |
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{%- if tools and tools is iterable and tools is not mapping %}
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| 46 |
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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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| 48 |
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{%- for tool in tools %}
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| 49 |
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{{- "\n" }}
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| 50 |
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{{- tool | tojson }}
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| 51 |
+
{%- endfor %}
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| 52 |
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{{- "\n</tools>" }}
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| 53 |
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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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| 54 |
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{%- if messages[0].role == 'system' %}
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| 55 |
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{%- set content = render_content(messages[0].content, false, true)|trim %}
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| 56 |
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{%- if content %}
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| 57 |
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{{- '\n\n' + content }}
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| 58 |
+
{%- endif %}
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| 59 |
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{%- endif %}
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| 60 |
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{{- '<|im_end|>\n' }}
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| 61 |
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{%- else %}
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| 62 |
+
{%- if messages[0].role == 'system' %}
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| 63 |
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{%- set content = render_content(messages[0].content, false, true)|trim %}
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| 64 |
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{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
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| 65 |
+
{%- endif %}
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| 66 |
+
{%- endif %}
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| 67 |
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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| 68 |
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{%- for message in messages[::-1] %}
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| 69 |
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{%- set index = (messages|length - 1) - loop.index0 %}
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| 70 |
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{%- if ns.multi_step_tool and message.role == "user" %}
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| 71 |
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{%- set content = render_content(message.content, false)|trim %}
|
| 72 |
+
{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
|
| 73 |
+
{%- set ns.multi_step_tool = false %}
|
| 74 |
+
{%- set ns.last_query_index = index %}
|
| 75 |
+
{%- endif %}
|
| 76 |
+
{%- endif %}
|
| 77 |
+
{%- endfor %}
|
| 78 |
+
{%- if ns.multi_step_tool %}
|
| 79 |
+
{{- raise_exception('No user query found in messages.') }}
|
| 80 |
+
{%- endif %}
|
| 81 |
+
{%- for message in messages %}
|
| 82 |
+
{%- set content = render_content(message.content, true)|trim %}
|
| 83 |
+
{%- if message.role == "system" %}
|
| 84 |
+
{%- if not loop.first %}
|
| 85 |
+
{{- raise_exception('System message must be at the beginning.') }}
|
| 86 |
+
{%- endif %}
|
| 87 |
+
{%- elif message.role == "user" %}
|
| 88 |
+
{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
|
| 89 |
+
{%- elif message.role == "assistant" %}
|
| 90 |
+
{%- set reasoning_content = '' %}
|
| 91 |
+
{%- if message.reasoning_content is string %}
|
| 92 |
+
{%- set reasoning_content = message.reasoning_content %}
|
| 93 |
+
{%- else %}
|
| 94 |
+
{%- if '</think>' in content %}
|
| 95 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 96 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 97 |
+
{%- endif %}
|
| 98 |
+
{%- endif %}
|
| 99 |
+
{%- set reasoning_content = reasoning_content|trim %}
|
| 100 |
+
{%- if (preserve_thinking is defined and preserve_thinking is true) or (loop.index0 > ns.last_query_index) %}
|
| 101 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
|
| 102 |
+
{%- else %}
|
| 103 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 104 |
+
{%- endif %}
|
| 105 |
+
{%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
|
| 106 |
+
{%- for tool_call in message.tool_calls %}
|
| 107 |
+
{%- if tool_call.function is defined %}
|
| 108 |
+
{%- set tool_call = tool_call.function %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{%- if loop.first %}
|
| 111 |
+
{%- if content|trim %}
|
| 112 |
+
{{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 113 |
+
{%- else %}
|
| 114 |
+
{{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 115 |
+
{%- endif %}
|
| 116 |
+
{%- else %}
|
| 117 |
+
{{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
|
| 118 |
+
{%- endif %}
|
| 119 |
+
{%- if tool_call.arguments is defined %}
|
| 120 |
+
{%- for args_name, args_value in tool_call.arguments|items %}
|
| 121 |
+
{{- '<parameter=' + args_name + '>\n' }}
|
| 122 |
+
{%- set args_value = args_value | string if args_value is string else args_value | tojson | safe %}
|
| 123 |
+
{{- args_value }}
|
| 124 |
+
{{- '\n</parameter>\n' }}
|
| 125 |
+
{%- endfor %}
|
| 126 |
+
{%- endif %}
|
| 127 |
+
{{- '</function>\n</tool_call>' }}
|
| 128 |
+
{%- endfor %}
|
| 129 |
+
{%- endif %}
|
| 130 |
+
{{- '<|im_end|>\n' }}
|
| 131 |
+
{%- elif message.role == "tool" %}
|
| 132 |
+
{%- if loop.previtem and loop.previtem.role != "tool" %}
|
| 133 |
+
{{- '<|im_start|>user' }}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '\n<tool_response>\n' }}
|
| 136 |
+
{{- content }}
|
| 137 |
+
{{- '\n</tool_response>' }}
|
| 138 |
+
{%- if not loop.last and loop.nextitem.role != "tool" %}
|
| 139 |
+
{{- '<|im_end|>\n' }}
|
| 140 |
+
{%- elif loop.last %}
|
| 141 |
+
{{- '<|im_end|>\n' }}
|
| 142 |
+
{%- endif %}
|
| 143 |
+
{%- else %}
|
| 144 |
+
{{- raise_exception('Unexpected message role.') }}
|
| 145 |
+
{%- endif %}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- if add_generation_prompt %}
|
| 148 |
+
{{- '<|im_start|>assistant\n' }}
|
| 149 |
+
{%- if enable_thinking is defined and enable_thinking is false %}
|
| 150 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 151 |
+
{%- else %}
|
| 152 |
+
{{- '<think>\n' }}
|
| 153 |
+
{%- endif %}
|
| 154 |
+
{%- endif %}
|
config.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
generation_config.json
ADDED
|
@@ -0,0 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"bos_token_id": 248044,
|
| 3 |
+
"do_sample": true,
|
| 4 |
+
"eos_token_id": [
|
| 5 |
+
248046,
|
| 6 |
+
248044
|
| 7 |
+
],
|
| 8 |
+
"pad_token_id": 248044,
|
| 9 |
+
"temperature": 1.0,
|
| 10 |
+
"top_k": 20,
|
| 11 |
+
"top_p": 0.95
|
| 12 |
+
}
|
model-00001-of-00003.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b335e9e2d0d16a511f881cf579dfac42076f3ddcdba0522bc2b4bbf19a8e35b3
|
| 3 |
+
size 4273688694
|
model-00002-of-00003.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c60721ee95003ce09eb887cfb2a18b4d99a47f74803ddcbd2646e40378a3d0ba
|
| 3 |
+
size 4267576969
|
model-00003-of-00003.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0bcf95ef86f03f683180f136fd4ffbe1cd8011a5e00eaa979a73e15be01b287d
|
| 3 |
+
size 3713971718
|
model.safetensors.index.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
optiq_metadata.json
ADDED
|
The diff for this file is too large to render.
See raw diff
|
|
|
tokenizer.json
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523
|
| 3 |
+
size 19989325
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,33 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": false,
|
| 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 |
+
"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,
|
| 27 |
+
"tokenizer_class": "Qwen2Tokenizer",
|
| 28 |
+
"tool_parser_type": "qwen3_coder",
|
| 29 |
+
"unk_token": null,
|
| 30 |
+
"video_token": "<|video_pad|>",
|
| 31 |
+
"vision_bos_token": "<|vision_start|>",
|
| 32 |
+
"vision_eos_token": "<|vision_end|>"
|
| 33 |
+
}
|