commit b87ca02ccb8293fb0637595661567576e8b13d61
Author: ModelHub XC <noreply@modelhub.org.cn>
Date:   Mon Jul 27 07:05:10 2026 +0800

    初始化项目，由ModelHub XC社区提供模型
    
    Model: melsmm/Spell-Corrector-RU-4B
    Source: Original Platform

diff --git a/.gitattributes b/.gitattributes
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+*.arrow filter=lfs diff=lfs merge=lfs -text
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+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
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diff --git a/Modelfile b/Modelfile
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--- /dev/null
+++ b/Modelfile
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+# ollama modelfile auto-generated by llamafactory
+
+FROM .
+
+TEMPLATE """{{ if .System }}<|im_start|>system
+{{ .System }}<|im_end|>
+{{ end }}{{ range .Messages }}{{ if eq .Role "user" }}<|im_start|>user
+{{ .Content }}<|im_end|>
+<|im_start|>assistant
+{{ else if eq .Role "assistant" }}{{ .Content }}<|im_end|>
+{{ end }}{{ end }}"""
+
+PARAMETER stop "<|im_end|>"
+PARAMETER num_ctx 4096
diff --git a/README.md b/README.md
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--- /dev/null
+++ b/README.md
@@ -0,0 +1,177 @@
+---
+license: apache-2.0
+language:
+- ru
+base_model:
+- RefalMachine/RuadaptQwen3-4B-Instruct
+datasets:
+- melsmm/spell-correction-ru
+- ai-forever/spellcheck_punctuation_benchmark
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- spell-correction
+- spelling-correction
+- punctuation-restoration
+- grammatical-error-correction
+- russian
+- qwen3
+- lora
+---
+
+# Spell-Corrector-RU-4B
+
+**Spell-Corrector-RU-4B** — языковая модель для **автоматического исправления орфографических, пунктуационных и регистровых ошибок** в русскоязычных текстах.
+
+Модель дообучена на базе [`RefalMachine/RuadaptQwen3-4B-Instruct`](https://huggingface.co/RefalMachine/RuadaptQwen3-4B-Instruct) (адаптированная под русский язык версия [`Qwen/Qwen3-4B-Instruct-2507`](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507)) методом **LoRA** в фреймворке [LLaMA-Factory](https://github.com/hiyouga/LLaMA-Factory). LoRA-адаптер уже **смержен** с базовой моделью — её можно использовать напрямую.
+
+📦 **Код, ноутбуки и полное описание проекта:** [github.com/melsmm/llm-spell-corrector](https://github.com/melsmm/llm-spell-corrector)
+📚 **Датасеты для обучения:** [`melsmm/spell-correction-ru`](https://huggingface.co/datasets/melsmm/spell-correction-ru)
+
+## Для чего модель
+
+Модель принимает текст с ошибками и возвращает его исправленную версию. Она умеет:
+
+- 🔤 исправлять **орфографические** ошибки и опечатки;
+- ❓ восстанавливать и исправлять **пунктуацию**;
+- 🔠 восстанавливать **регистр** букв (заглавные/строчные) и букву «ё».
+
+Основное преимущество перед существующими решениями (например, [SAGE](https://github.com/ai-forever/sage) на архитектуре T5) — **высокая скорость инференса** (через [vLLM](https://github.com/vllm-project/vllm), ~в 6 раз быстрее), простота внедрения в продакшен через OpenAI-совместимый API и лёгкость дообучения под новые домены с помощью LoRA.
+
+## На чём обучалась
+
+Обучение проходило в **две стадии**:
+
+| Стадия | Датасет | Объём | Описание |
+| --- | --- | --- | --- |
+| **Stage 1** | `synth_spell_correction_1m` | ~1 млн | Синтетические ошибки, внесённые в чистые корпусы (`nerus`, `gazeta`, `wikipedia`) с помощью [SAGE](https://github.com/ai-forever/sage) (`SBSC`, `CharAug`, `WordAug`) и собственного алгоритма пунктуационной порчи. |
+| **Stage 2** | `spell_correction_30k` | ~30 тыс. | Объединение готовых пар «ошибка → исправление» из открытых датасетов (RUSpellRU, MultidomainGold, GEC). |
+
+Сначала модель учится на большом объёме разнообразных синтетических ошибок, затем «дошлифовывается» на меньшем, но более качественном наборе реальных пар. Оба датасета доступны в репозитории [`melsmm/spell-correction-ru`](https://huggingface.co/datasets/melsmm/spell-correction-ru).
+
+**Гиперпараметры LoRA:** rank=32, alpha=64, dropout=0, bf16, cutoff length=4000.
+
+## Использование
+
+### Промпт
+
+Модель ожидает следующий формат запроса:
+
+```
+Исходный текст:
+{текст с ошибками}
+
+Отредактируй исходный текст, исправив ошибки.
+```
+
+Рекомендуемые параметры генерации: `temperature=0.1`, `top_p=0.7`.
+
+### Через `transformers`
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "melsmm/Spell-Corrector-RU-4B"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto")
+
+text = "привет как дила, что делаеш севодня"
+prompt = f"Исходный текст:\n{text}\n\nОтредактируй исходный текст, исправив ошибки."
+
+messages = [{"role": "user", "content": prompt}]
+inputs = tokenizer.apply_chat_template(
+    messages, add_generation_prompt=True, return_tensors="pt"
+).to(model.device)
+
+outputs = model.generate(inputs, max_new_tokens=512, temperature=0.1, top_p=0.7, do_sample=True)
+print(tokenizer.decode(outputs[0][inputs.shape[1]:], skip_special_tokens=True))
+```
+
+### Через vLLM (рекомендуется для продакшена)
+
+Запуск OpenAI-совместимого сервера:
+
+```bash
+vllm serve melsmm/Spell-Corrector-RU-4B \
+    --gpu-memory-utilization 0.95 \
+    --host 0.0.0.0 \
+    --port 9900 \
+    --served-model-name spell_correction \
+    --max-model-len 4096
+```
+
+Обращение к серверу:
+
+```python
+from openai import OpenAI
+
+client = OpenAI(base_url="http://localhost:9900/v1", api_key="EMPTY")
+
+text = "привет как дила"
+resp = client.chat.completions.create(
+    model="spell_correction",
+    messages=[{"role": "user", "content":
+        f"Исходный текст:\n{text}\n\nОтредактируй исходный текст, исправив ошибки."}],
+    temperature=0.1,
+    top_p=0.7,
+)
+print(resp.choices[0].message.content)
+```
+
+## Качество
+
+Оценка на бенчмарке [`ai-forever/spellcheck_punctuation_benchmark`](https://huggingface.co/datasets/ai-forever/spellcheck_punctuation_benchmark) (F1 по орфографии / пунктуации / регистру):
+
+### RUSpellRU
+
+| Model | F1 (spell) | F1 (punc) | F1 (case) |
+| --- | --: | --: | --: |
+| **Spell-Corrector-RU-4B** | 64.7 | 84.5 | 94.2 |
+| sage-fredt5-large | 84.5 | 86.8 | 94.7 |
+| gpt-4 | 64.0 | 83.2 | 90.9 |
+| gpt-3.5-turbo | 42.7 | 73.7 | 79.0 |
+
+### MultidomainGold
+
+| Model | F1 (spell) | F1 (punc) | F1 (case) |
+| --- | --: | --: | --: |
+| **Spell-Corrector-RU-4B** | 62.6 | 66.5 | 80.0 |
+| sage-fredt5-large | 77.6 | 67.7 | 79.3 |
+| gpt-4 | 37.0 | 56.0 | 60.0 |
+| gpt-3.5-turbo | 27.1 | 36.2 | 49.1 |
+
+### MedSpellchecker
+
+| Model | F1 (spell) | F1 (punc) | F1 (case) |
+| --- | --: | --: | --: |
+| **Spell-Corrector-RU-4B** | 42.8 | 70.4 | 76.3 |
+| sage-fredt5-large | 72.3 | 70.3 | 82.1 |
+| gpt-4 | 49.6 | 71.9 | 67.1 |
+| gpt-3.5-turbo | 22.3 | 59.8 | 32.3 |
+
+### GitHubTypoCorpusRu
+
+| Model | F1 (spell) | F1 (punc) | F1 (case) |
+| --- | --: | --: | --: |
+| **Spell-Corrector-RU-4B** | 49.7 | 34.8 | 45.8 |
+| sage-fredt5-large | 59.5 | 42.6 | 42.7 |
+| gpt-4 | 35.7 | 38.2 | 30.2 |
+| gpt-3.5-turbo | 29.4 | 28.7 | 25.3 |
+
+> Полные таблицы (Precision / Recall / F1 + сравнение со Stage 1) — в [репозитории проекта](https://github.com/melsmm/llm-spell-corrector#-результаты).
+
+### Скорость инференса
+
+На RUSpellRU (2008 примеров) через vLLM: **45 с** (0.022 с/пример) против **284 с** (0.141 с/пример) у sage-fredt5-large — **~в 6 раз быстрее**.
+
+## Ограничения
+
+- Модель уступает SAGE по орфографии на ряде доменов, но конкурентна по пунктуации и регистру.
+- Качество может снижаться на узкоспециализированных доменах (например, медицина) — там рекомендуется дообучение под домен с помощью LoRA.
+- Модель работает с русским языком; для других языков не предназначена.
+
+## Ссылки
+
+- 🔗 **Проект на GitHub:** https://github.com/melsmm/llm-spell-corrector
+- 🤗 **Датасеты:** https://huggingface.co/datasets/melsmm/spell-correction-ru
+- 🧩 **Базовая модель:** https://huggingface.co/RefalMachine/RuadaptQwen3-4B-Instruct
diff --git a/chat_template.jinja b/chat_template.jinja
new file mode 100644
index 0000000..34bd053
--- /dev/null
+++ b/chat_template.jinja
@@ -0,0 +1,52 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\n# 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 %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.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 %}
diff --git a/config.json b/config.json
new file mode 100644
index 0000000..3f1df01
--- /dev/null
+++ b/config.json
@@ -0,0 +1,71 @@
+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": null,
+  "dtype": "bfloat16",
+  "eos_token_id": 146215,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 2560,
+  "initializer_range": 0.02,
+  "intermediate_size": 9728,
+  "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": 262144,
+  "max_window_layers": 36,
+  "model_type": "qwen3",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 8,
+  "pad_token_id": 146213,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 5000000,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.0.0",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 146260
+}
diff --git a/generation_config.json b/generation_config.json
new file mode 100644
index 0000000..fe91d10
--- /dev/null
+++ b/generation_config.json
@@ -0,0 +1,9 @@
+{
+  "do_sample": true,
+  "eos_token_id": 146215,
+  "pad_token_id": 146213,
+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "5.0.0"
+}
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new file mode 100644
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