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Model: KiwiMate/KiwiMate-Mini-Preview
Source: Original Platform

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KiwiMate-Mini-Preview-MODEL_CARD.md

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+---
+language: en
+license: apache-2.0
+base_model: meta-llama/Llama-3.2-3B-Instruct
+tags:
+  - unsloth
+  - text-generation-inference
+  - conversational
+  - gguf
+  - llama
+datasets:
+  - KiwiMate/KiwiMate-Mini-training
+pipeline_tag: text-generation
+---
+
+# KiwiMate-Mini-Preview
+
+**KiwiMate-Mini-Preview** is a lightweight, New Zealand–flavoured conversational language model, fine-tuned for the [KiwiMate](https://kiwimate.net) AI companion app. It is the smallest model in the KiwiMate model family and is designed for fast, low-cost inference on the app's free and lower-tier subscription plans.
+
+> ⚠️ **Preview status:** This is a prototype release. The name reflects its preview status — expect breaking changes, retraining, and behavioural shifts before a stable v1 release.
+
+## Model Details
+
+| | |
+|---|---|
+| **Developed by** | KiwiMate / KyleCodeKiwi |
+| **Base model** | Llama 3.2 3B Instruct |
+| **Architecture** | Llama |
+| **Parameters** | ~3.21B |
+| **Fine-tuning framework** | [Unsloth](https://github.com/unslothai/unsloth) |
+| **License** | Apache 2.0 |
+| **Languages** | English (with New Zealand English and Te Reo Māori vocabulary coverage) |
+| **Model class** | `AutoModelForCausalLM` |
+
+## Intended Use
+
+KiwiMate-Mini-Preview is intended as the default conversational backend for the KiwiMate app, providing:
+
+- General-purpose chat and assistant-style conversation
+- New Zealand cultural and "Kiwi" context awareness (slang, geography, fun facts)
+- Light Te Reo Māori vocabulary recognition and use
+- Lore and knowledge specific to the KiwiMate app itself ("KiwiMate Origin" data)
+- Lightweight knowledge support for in-app mini-games
+
+It is **not** intended for high-stakes, medical, legal, or financial advice, and should not be relied on as an authoritative source on Māori language or tikanga — for genuinely sensitive Te Reo or cultural content, defer to community-governed resources.
+
+## Training Data
+
+Fine-tuned on the [`KiwiMate/KiwiMate-Mini-training`](https://huggingface.co/datasets/KiwiMate/KiwiMate-Mini-training) dataset, organised into categories including:
+
+- NZ English
+- Te Reo Māori
+- KiwiMate Origin (app-specific lore/identity)
+- NZ Fun Facts
+- MiniGame Knowledge
+
+## Files & Quantizations
+
+Distributed as `safetensors` (full precision) and GGUF quantizations for efficient local/edge inference:
+
+| Format | Use case |
+|---|---|
+| F16 | Highest fidelity, largest size |
+| Q6_K | Near-lossless, smaller footprint |
+| Q4_K_M | Balanced quality/size — recommended default for on-device use |
+| Q2_K_L | Smallest footprint, lowest fidelity |
+
+## Deployment
+
+Served in production via a Hugging Face Inference Endpoint on a T4 GPU with scale-to-zero, fronted by a Supabase Edge Function (OpenAI-compatible proxy) that routes KiwiMate app traffic to this and other KiwiMate model endpoints behind a single API.
+
+### Known Limitations
+
+- A server-side mitigation is in place for an occasional role-bleed / over-generation issue (the model sometimes continuing past `<|eot_id|>`), handled via stop-sequence aliases and trimming at the proxy layer.
+- The long-term fix — adding `<|eot_id|>` (token ID 128009) properly to the training loss and `generation_config.json` — is planned for a future retraining pass rather than this preview.
+- As a 3B-parameter model, reasoning depth and factual reliability are limited compared to larger models; it is tuned for speed and personality over raw capability.
+
+## License
+
+Released under the Apache 2.0 license, consistent with the open weights commitment for the KiwiMate model family.

README.md

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+---
+language: en
+license: apache-2.0
+base_model: meta-llama/Llama-3.2-3B-Instruct
+tags:
+  - unsloth
+  - text-generation-inference
+  - conversational
+  - gguf
+  - llama
+datasets:
+  - KiwiMate/KiwiMate-Mini-training
+pipeline_tag: text-generation
+---
+
+# KiwiMate-Mini-Preview
+
+**KiwiMate-Mini-Preview** is a lightweight, New Zealand–flavoured conversational language model, fine-tuned for the [KiwiMate](https://kiwimate.net) AI companion app. It is the smallest model in the KiwiMate model family and is designed for fast, low-cost inference on the app's free and lower-tier subscription plans.
+
+> ⚠️ **Preview status:** This is a prototype release. The name reflects its preview status — expect breaking changes, retraining, and behavioural shifts before a stable v1 release.
+
+## Model Details
+
+| | |
+|---|---|
+| **Developed by** | KiwiMate / KyleCodeKiwi |
+| **Base model** | Llama 3.2 3B Instruct |
+| **Architecture** | Llama |
+| **Parameters** | ~3.21B |
+| **Fine-tuning framework** | [Unsloth](https://github.com/unslothai/unsloth) |
+| **License** | Apache 2.0 |
+| **Languages** | English (with New Zealand English and Te Reo Māori vocabulary coverage) |
+| **Model class** | `AutoModelForCausalLM` |
+
+## Intended Use
+
+KiwiMate-Mini-Preview is intended as the default conversational backend for the KiwiMate app, providing:
+
+- General-purpose chat and assistant-style conversation
+- New Zealand cultural and "Kiwi" context awareness (slang, geography, fun facts)
+- Light Te Reo Māori vocabulary recognition and use
+- Lore and knowledge specific to the KiwiMate app itself ("KiwiMate Origin" data)
+- Lightweight knowledge support for in-app mini-games
+
+It is **not** intended for high-stakes, medical, legal, or financial advice, and should not be relied on as an authoritative source on Māori language or tikanga — for genuinely sensitive Te Reo or cultural content, defer to community-governed resources.
+
+## Training Data
+
+Fine-tuned on the [`KiwiMate/KiwiMate-Mini-training`](https://huggingface.co/datasets/KiwiMate/KiwiMate-Mini-training) dataset, organised into categories including:
+
+- NZ English
+- Te Reo Māori
+- KiwiMate Origin (app-specific lore/identity)
+- NZ Fun Facts
+- MiniGame Knowledge
+
+## Files & Quantizations
+
+Distributed as `safetensors` (full precision) and GGUF quantizations for efficient local/edge inference:
+
+| Format | Use case |
+|---|---|
+| F16 | Highest fidelity, largest size |
+| Q6_K | Near-lossless, smaller footprint |
+| Q4_K_M | Balanced quality/size — recommended default for on-device use |
+| Q2_K_L | Smallest footprint, lowest fidelity |
+
+## Deployment
+
+Served in production via a Hugging Face Inference Endpoint on a T4 GPU with scale-to-zero, fronted by a Supabase Edge Function (OpenAI-compatible proxy) that routes KiwiMate app traffic to this and other KiwiMate model endpoints behind a single API.
+
+### Known Limitations
+
+- A server-side mitigation is in place for an occasional role-bleed / over-generation issue (the model sometimes continuing past `<|eot_id|>`), handled via stop-sequence aliases and trimming at the proxy layer.
+- The long-term fix — adding `<|eot_id|>` (token ID 128009) properly to the training loss and `generation_config.json` — is planned for a future retraining pass rather than this preview.
+- As a 3B-parameter model, reasoning depth and factual reliability are limited compared to larger models; it is tuned for speed and personality over raw capability.
+
+## License
+
+Released under the Apache 2.0 license, consistent with the open weights commitment for the KiwiMate model family.

chat_template.jinja

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+{{- bos_token }}
+{%- if custom_tools is defined %}
+    {%- set tools = custom_tools %}
+{%- endif %}
+{%- if not tools_in_user_message is defined %}
+    {%- set tools_in_user_message = true %}
+{%- endif %}
+{%- if not date_string is defined %}
+    {%- if strftime_now is defined %}
+        {%- set date_string = strftime_now("%d %b %Y") %}
+    {%- else %}
+        {%- set date_string = "26 Jul 2024" %}
+    {%- endif %}
+{%- endif %}
+{%- if not tools is defined %}
+    {%- set tools = none %}
+{%- endif %}
+
+{#- This block extracts the system message, so we can slot it into the right place. #}
+{%- if messages[0]['role'] == 'system' %}
+    {%- set system_message = messages[0]['content']|trim %}
+    {%- set messages = messages[1:] %}
+{%- else %}
+    {%- set system_message = "" %}
+{%- endif %}
+
+{#- System message #}
+{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
+{%- if tools is not none %}
+    {{- "Environment: ipython\n" }}
+{%- endif %}
+{{- "Cutting Knowledge Date: December 2023\n" }}
+{{- "Today Date: " + date_string + "\n\n" }}
+{%- if tools is not none and not tools_in_user_message %}
+    {{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+{%- endif %}
+{{- system_message }}
+{{- "<|eot_id|>" }}
+
+{#- Custom tools are passed in a user message with some extra guidance #}
+{%- if tools_in_user_message and not tools is none %}
+    {#- Extract the first user message so we can plug it in here #}
+    {%- if messages | length != 0 %}
+        {%- set first_user_message = messages[0]['content']|trim %}
+        {%- set messages = messages[1:] %}
+    {%- else %}
+        {{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
+{%- endif %}
+    {{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
+    {{- "Given the following functions, please respond with a JSON for a function call " }}
+    {{- "with its proper arguments that best answers the given prompt.\n\n" }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+    {{- first_user_message + "<|eot_id|>"}}
+{%- endif %}
+
+{%- for message in messages %}
+    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
+        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
+    {%- elif 'tool_calls' in message %}
+        {%- if not message.tool_calls|length == 1 %}
+            {{- raise_exception("This model only supports single tool-calls at once!") }}
+        {%- endif %}
+        {%- set tool_call = message.tool_calls[0].function %}
+        {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+        {{- '{"name": "' + tool_call.name + '", ' }}
+        {{- '"parameters": ' }}
+        {{- tool_call.arguments | tojson }}
+        {{- "}" }}
+        {{- "<|eot_id|>" }}
+    {%- elif message.role == "tool" or message.role == "ipython" %}
+        {{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
+        {%- if message.content is mapping or message.content is iterable %}
+            {{- message.content | tojson }}
+        {%- else %}
+            {{- message.content }}
+        {%- endif %}
+        {{- "<|eot_id|>" }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
+{%- endif %}

config.json

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+{
+    "architectures": [
+        "LlamaForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 128000,
+    "torch_dtype": "bfloat16",
+    "eos_token_id": 128009,
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 3072,
+    "initializer_range": 0.02,
+    "intermediate_size": 8192,
+    "max_position_embeddings": 131072,
+    "mlp_bias": false,
+    "model_type": "llama",
+    "num_attention_heads": 24,
+    "num_hidden_layers": 28,
+    "num_key_value_heads": 8,
+    "pad_token_id": 128004,
+    "pretraining_tp": 1,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": {
+        "factor": 32.0,
+        "high_freq_factor": 4.0,
+        "low_freq_factor": 1.0,
+        "original_max_position_embeddings": 8192,
+        "rope_type": "llama3"
+    },
+    "rope_theta": 500000.0,
+    "tie_word_embeddings": true,
+    "unsloth_fixed": true,
+    "unsloth_version": "2026.5.2",
+    "use_cache": true,
+    "vocab_size": 128256
+}

generation_config.json

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+{
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "max_length": 262144,
+  "pad_token_id": 11,
+  "transformers_version": "5.0.0.dev0"
+}

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