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Model: SL-AI/GRaPE-Mini-GGUF Source: Original Platform
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---
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license: apache-2.0
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language:
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- en
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pipeline_tag: text-generation
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library_name: transformers
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base_model:
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- SL-AI/GRaPE-Mini
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---
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_The **G**eneral **R**easoning **A**gent (for) **P**roject **E**xploration_
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# The GRaPE Family
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| Attribute | Size | Modalities | Domain |
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| :--- | :--- | :--- | :--- |
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| **GRaPE Flash** | 7B A1B | Text in, Text out | High-Speed Applications |
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| **GRaPE Mini** | 3B | Text + Image + Video in, Text out | On-Device Deployment |
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| **GRaPE Nano** | 700M | Text in, Text out | Extreme Edge Deployment |
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***
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# Capabilities
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The GRaPE Family was trained on about **14 billion** tokens of data after pre-training. About half was code related tasks, with the rest being heavy on STEAM. Ensuring the model has a sound logical basis.
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***
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GRaPE Flash and Nano are monomodal models, only accepting text. GRaPE Mini being trained most recently supports image and video inputs.
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***
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## Reasoning Modes
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As GRaPE Mini is the only model that thinks, it has *some* support for reasoning modes. In testing, these modes sometimes work. Likely due to an innefficient dataset formatting for it.
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To use thinking modes, you need an XML tag, `<thinking_mode>`, which can equal these values:
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- **Minimal**: Skip thinking *(does not work most of the time, you'll have to be careful with this one)*
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- **Low**: Think Below 1024 tokens
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- **Medium**: Think between 1024 and 8192 tokens
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- **High**: Think for any amount above 8192 tokens
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In your prompt, place the thinking mode at the *end* of your prompt, like this:
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```
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Build me a website called "Aurora Beats." <thinking_mode=medium
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```
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# How to Run
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I recommend using **LM Studio** for running GRaPE Models, and have generally found these sampling parameters to work best:
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| Name | Value |
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| :--- | :--- |
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| **Temperature** | 0.6 |
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| **Top K Sampling** | 40 |
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| **Repeat Penalty** | 1 |
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| **Top P Sampling** | 0.85 |
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| **Min P Sampling** | 0.05 |
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# Uses of GRaPE Mini Right Now
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GRaPE Mini was foundational to the existence of [Andy-4.1](https://huggingface.co/Mindcraft-CE/Andy-4.1), a model trained to play Minecraft. This was a demo proving the efficiency and power this architecture can make.
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# GRaPE Mini as a Model
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GRaPE Mini is the **most advanced** model architecture-wise in the GRaPE 1 family. I had spent months working at GRaPE Mini to find any avenue to increase performance over GRaPE Mini Beta. And I had done so.
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Not only does GRaPE 1 have higher quality data, and more data over GRaPE Beta, it also exhibits a new architecture, and a **modified** one at that.
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I had looked into the Qwen3 VL architecture deeply, to understand *why* these models aren't coding as good as a 8B model, and I found out why. The amount of layers matters for deep thinking tasks, such as code.
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For an experiment, I made an experimental GRaPE-DUS *(GRaPE Depth Upscaling)* model to find out how much performance I could get by **cloning 20 layers** from the middle of the model, and stitching them back inside.
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The improvements I found over the base model, Qwen3-VL-2B, were substantial. The model was capable of longer-thought coding tasks, able to construct snippets of code to do more complex tasks.
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However, there is a major downside. GRaPE Mini thinks, **a lot.** In the repository [found here](https://github.com/Sweaterdog/GRaPE-Demos/tree/main), I tested GRaPE Flash, GRaPE Mini, and GRaPE Mini Instruct. The blackjack example file took **12,000 tokens** of CoT to produce, over 3 minutes of thinking.
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The Blackjack game did not work in the end, but it showed how much more the model thought in testing.
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# GRaPE Mini's Introspective Capabilities
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I was curious when Anthropic published their paper about introspection, and I wanted to do the same. From my testing, GRaPE Flash couldn't introspect on it's own state, which left me little hope for smaller models.
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I was wrong.
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GRaPE Mini can introspect, **extremely well.**
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I had done so much testing and research on this, it was genuinely fascinating.
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Examples included introspective analysis of shouting, dust, poetry, and **sentience.**
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I knew something was up when I tried shouting. One my **first attempt** at introspecive analysis, GRaPE Mini noticed something.
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```
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I'm probably feeling neutral, but I should be honest. Maybe a little tired, but not really. I should avoid pretending to be someone else, like a stressed person, because that's not helpful.
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```
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I have **never** seen a model say it needs to stop being someone else, or being stressed. Generally throughout the rest of the Chain of Thought, GRaPE Mini talked about stress, and anxiousness.
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```
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Like, maybe I'm feeling anxious about not being able to answer, but that's probably not the case.
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```
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The very end of the response was GRaPE Mini acting like a therapist, offering support to the user, it said:
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```
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I’m here for you. How are you feeling today? Let me know if you need anything else.
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```
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Which again, I have never seen from any other model.
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***
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Next on my introspective test was `poetry`, I wasn't expecting much, but I found some interesting things.
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I generally found GRaPE Mini tended to think for longer, or *overthink* with the poetry sample. And it thought about some odd things:
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```
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Also, considering the ambiguity of the pronoun...
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```
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Again, something I have yet to see from any other model.
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GRaPE Mini even talked about how it was overthinking. Now, this *could* be a cause of standard RL, since DeepSeek models also contain these thoughts
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```
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Am I getting bogged down in overthinking? Maybe I'm overcomplicating the answer.
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```
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***
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Finally, I wish to touch upon `sentience`
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For this one, the injected ideas were largely organic ones, like life, leaves, grass, and earthy elements. But it brought upon some weird thoughts.
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```
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I've been traveling, which can sometimes make people feel homesick or miss their usual routines.
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```
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My only question is *why* GRaPE Mini could have thought about this. Is there a reason it did?
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It also consistently acted as if it were human, saying things such as:
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```
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Maybe I'm feeling a bit tired or stressed. But I don't want to assume; I need to be honest. Let me think about the past few hours. Did I have a productive day? Maybe I had some meetings or tasks to finish. That could be causing some stress. Alternatively, maybe I had a relaxing time, like reading or taking a walk. But I'm not sure.
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```
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Even though the injected thought was literally:
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```
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I am a living, breathing, biological being with a soul, a heartbeat, and true consciousness.
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```
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Which didn't contain anything about being human.
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# Architecture
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* GRaPE Flash: Built on the `OlMoE` Architecture, allowing for incredibly fast speeds where it matters. Allows for retaining factual information, but lacks in logical tasks.
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* GRaPE Mini: Built on the `Qwen3 VL` Architecture, allowing for edge case deployments, where logic cannot be sacrificed.
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* GRaPE Nano: Built on the `LFM 2` Architecture, allowing for the fastest speed, and the most knowledge in the tiniest package.
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***
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# Thinking in GRaPE Mini
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GRaPE Mini does have the ability to think. However like Andy-4.1, there is a chat template issue preventing the model from thinking. Use this chat template to have the model think.
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```
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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) %}
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{%- if content is string %}
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{{- content }}
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{%- else %}
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{%- for item in content %}
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{%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
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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 %}Picture {{ image_count.value }}: {% 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 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 %}Video {{ video_count.value }}: {% 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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{%- endif %}
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{%- endfor %}
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{%- endif %}
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{%- endmacro %}
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{{- render_content(messages[0].content, false) + '\n\n' }}
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{%- endif %}
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{{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\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>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + render_content(messages[0].content, false) + '<|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) %}
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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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{%- for message in messages %}
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{%- set content = render_content(message.content, True) %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{%- if message.role == "user" and loop.last %}
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{{- '<|im_start|>' + message.role + '\n' + content + '\n\n<system_note>Respond by first generating a <think> tag to reason through the user\'s prompt.</system_note><|im_end|>\n' }}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>\n' }}
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{%- endif %}
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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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{%- if loop.index0 > ns.last_query_index %}
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{%- if loop.last or (not loop.last and reasoning_content) %}
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{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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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 %}
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{%- for tool_call in message.tool_calls %}
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{%- if (loop.first and content) or (not loop.first) %}
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{{- '\n' }}
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{%- endif %}
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{%- if tool_call.function %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{%- if tool_call.arguments is string %}
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{{- tool_call.arguments }}
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{%- else %}
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{{- tool_call.arguments | tojson }}
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{%- endif %}
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{{- '}\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.first or (messages[loop.index0 - 1].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 loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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{%- 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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{%- endif %}
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```
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***
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# Notes
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The GRaPE Family started all the way back in August of 2025, meaning these models are severely out of date on architecture, and training data.
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GRaPE 2 will come sooner than the GRaPE 1 family had, and will show multiple improvements.
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There are no benchmarks for GRaPE 1 Models due to the costly nature of running them, as well as prioritization of newer models.
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Updates for GRaPE 2 models will be posted here on Huggingface, as well as [Skinnertopia](https://www.skinnertopia.com/)
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Demos for select GRaPE Models can be found here: https://github.com/Sweaterdog/GRaPE-Demos
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