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Model: jburnford/dyslexic-writer-qwen3-4b
Source: Original Platform

.gitattributes

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+tokenizer.json filter=lfs diff=lfs merge=lfs -text
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+Qwen3-4B-q5_k_m.gguf filter=lfs diff=lfs merge=lfs -text
+Qwen3-4B-q6_k.gguf filter=lfs diff=lfs merge=lfs -text

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README.md

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+---
+language: en
+license: apache-2.0
+tags:
+  - spelling-correction
+  - dyslexia
+  - text-correction
+  - education
+base_model: Qwen/Qwen3-4B
+pipeline_tag: text-generation
+---
+
+# Dyslexic Writer - Qwen3-4B
+
+Fine-tuned **Qwen/Qwen3-4B** for spelling and grammar correction, optimized for dyslexic writers.
+
+## Performance
+
+| Metric | Score |
+|--------|-------|
+| Exact Match Accuracy | 85.6% |
+| Error Fix Rate | 80.4% |
+| No-Error Preservation | 99.3% |
+| F1 Score | 99.5% |
+
+Trained on ~495K examples including word pairs, sentence corrections, and paragraph-level error injection from synthetic stories.
+
+## Usage
+
+### With Ollama (GGUF)
+
+Download the Q4_K_M GGUF and create a Modelfile:
+
+```
+FROM ./dyslexic-writer-qwen3-4b-q4_k_m.gguf
+
+PARAMETER temperature 0
+PARAMETER num_predict 256
+
+SYSTEM You are a spelling correction assistant.
+
+TEMPLATE """<|im_start|>system
+{{ .System }}<|im_end|>
+<|im_start|>user
+{{ .Prompt }}<|im_end|>
+<|im_start|>assistant
+<think>
+
+</think>
+
+"""
+```
+
+### With Transformers
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("jburnford/dyslexic-writer-qwen3-4b")
+tokenizer = AutoTokenizer.from_pretrained("jburnford/dyslexic-writer-qwen3-4b")
+
+messages = [
+    {"role": "system", "content": "You are a spelling correction assistant."},
+    {"role": "user", "content": "Fix any spelling mistakes in this text. If there are no mistakes, output the text unchanged.\n\nI went to teh store."},
+]
+
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True, enable_thinking=False)
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=256, do_sample=False)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Model Variants
+
+| Model | GGUF Q4_K_M | Exact Match | Best For |
+|-------|-------------|-------------|----------|
+| [Qwen3-0.6B](https://huggingface.co/jburnford/dyslexic-writer-qwen3-0.6b) | ~460 MB | 78.8% | Mobile/embedded |
+| [Qwen3-1.7B](https://huggingface.co/jburnford/dyslexic-writer-qwen3-1.7b) | ~1.2 GB | 82.2% | Default |
+| [Qwen3-4B](https://huggingface.co/jburnford/dyslexic-writer-qwen3-4b) | ~2.5 GB | 85.6% | Best quality |

added_tokens.json

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+  "</tool_call>": 151658,
+  "</tool_response>": 151666,
+  "<think>": 151667,
+  "<tool_call>": 151657,
+  "<tool_response>": 151665,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
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+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
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+}

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 loop.last or (not loop.last and 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' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

config.json

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+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
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+  "hidden_act": "silu",
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+  "intermediate_size": 9728,
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+    "full_attention",
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+    "full_attention",
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+    "full_attention",
+    "full_attention",
+    "full_attention",
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+    "full_attention",
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+    "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",
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+  "num_hidden_layers": 36,
+  "num_key_value_heads": 8,
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+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
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+    "rope_type": "default"
+  },
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+  "tie_word_embeddings": true,
+  "transformers_version": "5.2.0",
+  "use_cache": false,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

eval_results.json

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+  "model": "Qwen3-4B",
+  "total_examples": 5000,
+  "exact_match_accuracy": 0.8564,
+  "error_detection": {
+    "precision": 0.9969188634029442,
+    "recall": 0.9921635434412266,
+    "f1": 0.994535519125683,
+    "true_positives": 2912,
+    "false_positives": 9,
+    "true_negatives": 1370,
+    "false_negatives": 23
+  },
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+  "no_error_accuracy": 0.9934735315445975,
+  "inference_speed_tokens_per_sec": 58.816495560243375,
+  "total_inference_time_sec": 1150.6635911464691,
+  "total_tokens_generated": 67678
+}

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+  "transformers_version": "5.2.0"
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