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Model: GMatherne/qwen3-8b-human-sft
Source: Original Platform

.gitattributes

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README.md

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+---
+license: apache-2.0
+base_model: unsloth/Qwen3-8B
+tags:
+  - qwen3
+  - qlora
+  - unsloth
+  - educational
+  - human-sounding
+language:
+  - en
+pipeline_tag: text-generation
+---
+
+# Qwen3-8B — Human-Sounding Educational Tutor (QLoRA)
+
+A QLoRA fine-tune of **Qwen3-8B** (non-thinking) trained to answer everyday
+educational/tutoring questions in **natural, human-sounding prose** — text that an
+AI-text detector (Pangram) reads as human-written rather than AI-generated.
+
+**This is a course/research artifact demonstrating "behavior from data," not a
+production tutor.** The target behavior is *voice*, and (see Evaluation) that voice
+is bought at a real cost in factual accuracy versus the untuned base — so do **not**
+use it as a source of factual authority.
+
+## What it does
+
+Given a student's question — explain a concept, help with an essay, correct a
+mistake — it responds the way a knowledgeable human would in a forum answer:
+conversational, direct, first-person, without the padding, hedging, list-scaffolding,
+and even pacing that give default AI writing away. It answers as an AI assistant (it
+never claims to be a person) and does not cite sources or add sign-offs.
+
+## Training
+
+- **Base:** `unsloth/Qwen3-8B`, run in **non-thinking** mode (`enable_thinking=False`).
+- **Method:** QLoRA (4-bit) via [Unsloth](https://github.com/unslothai/unsloth) —
+  LoRA `r=32`, `alpha=32`, dropout 0, all 7 attention+MLP projections; 2 epochs,
+  lr `2e-4`, ChatML template, `train_on_responses_only`.
+- **Data:** ~1,800 curated, heavily-cleaned **human** answers from StackExchange and
+  Reddit (ELI5 / AskScience / AskHistorians / topic SE sites), filtered to remove
+  forum scaffolding, fabricated citations, links, markdown, and non-English text.
+  The dataset is the real deliverable; training is a downstream button-press.
+- Two variants: **SFT** (the fine-tune) and **DPO** (a preference-tuning pass on top).
+
+## Evaluation (honest)
+
+LLM-as-judge (GPT-5) on 16 held-out education prompts, base vs tuned:
+
+| Model | Accuracy /5 | Info retention | Answers w/ ≥1 error | Confident fabrications |
+|---|---|---|---|---|
+| Qwen3-8B base (untuned) | **4.56** | 65% | 3/16 | 1 |
+| This model — SFT | 3.25 | 64% | 11/16 | 12 |
+| This model — DPO | 2.88 | 56% | 15/16 | 11 |
+
+**Human-ness (Pangram AI-detector): _[fill in after scoring]_** — this is the metric
+the model is optimized for; the base reads as ~100% AI.
+
+**Read this honestly:** fine-tuning for the human voice **lowers factual accuracy and
+raises fabrication rate** relative to the strong base model. It also degrades
+instruction-following on terse/format-constrained tasks (write code, "answer in one
+word", JSON) — it tends to over-explain. The defensible result is *reliable human
+voice in a small local model*, not raw capability.
+
+## Intended use & limitations
+
+- **Use:** research/education on data-driven behavior control; generating
+  human-reading educational prose where factual precision is not critical.
+- **Do not use** for authoritative facts, math, code, or format-constrained output.
+- May still occasionally read as AI on some prompts; may state confident but wrong
+  claims (a "forum register" side-effect).
+
+## Usage
+
+**Ollama (GGUF):**
+```
+ollama create qwen3-human -f Modelfile   # Modelfile FROM ./qwen3-human*.Q8_0.gguf
+ollama run qwen3-human
+```
+
+**Transformers:** load the merged weights and apply the ChatML chat template with the
+system prompt below; sample at `temperature=0.7, top_p=0.8, top_k=20,
+repetition_penalty=1.15`.
+
+**System prompt used in training/inference:**
+> You are a helpful AI tutor. You explain concepts clearly and accurately, covering
+> the actual mechanism or reasoning rather than a vague summary. You help with writing
+> and correct mistakes, in natural, plain language. You are an AI assistant — you never
+> claim to be a human, a person, or a product. Never cite specific studies, papers,
+> books, articles, authors, DOIs, or web links, and never invent a source or title —
+> explain things in your own words. Do not end with sign-offs like "hope this helps."
+
+## License
+
+Apache-2.0, inheriting the base model (`unsloth/Qwen3-8B`).

chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# 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>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\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" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if reasoning_content %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

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+{
+    "architectures": [
+        "Qwen3ForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": null,
+    "torch_dtype": "bfloat16",
+    "eos_token_id": 151645,
+    "head_dim": 128,
+    "hidden_act": "silu",
+    "hidden_size": 4096,
+    "initializer_range": 0.02,
+    "intermediate_size": 12288,
+    "layer_types": [
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention",
+        "full_attention"
+    ],
+    "max_position_embeddings": 40960,
+    "max_window_layers": 36,
+    "model_type": "qwen3",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 36,
+    "num_key_value_heads": 8,
+    "pad_token_id": 151654,
+    "rms_norm_eps": 1e-06,
+    "rope_parameters": {
+        "rope_theta": 1000000,
+        "rope_type": "default"
+    },
+    "sliding_window": null,
+    "tie_word_embeddings": false,
+    "unsloth_fixed": true,
+    "unsloth_version": "2026.7.2",
+    "use_cache": false,
+    "use_sliding_window": false,
+    "vocab_size": 151936
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "max_length": 40960,
+  "pad_token_id": 151654,
+  "temperature": 0.6,
+  "top_k": 20,
+  "top_p": 0.95,
+  "transformers_version": "5.5.0"
+}

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tokenizer.json

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+version https://git-lfs.github.com/spec/v1
+oid sha256:476870a1f2fb6f6a2759a6ede2383bf9d5d738f17844563b65c91965b722ae09
+size 11422924

tokenizer_config.json

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+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "is_local": true,
+  "model_max_length": 40960,
+  "pad_token": "<|vision_pad|>",
+  "padding_side": "right",
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+}