From f738becc719e50ef31bc0b0bc5b869bae173d7af Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sat, 4 Jul 2026 05:08:13 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: Vikhrmodels/Vikhr-YandexGPT-5-Lite-8B-it Source: Original Platform --- .gitattributes | 55 + LICENSE | 97 + README.md | 183 + config.json | 30 + configuration.json | 1 + generation_config.json | 6 + model-00001-of-00004.safetensors | 3 + model-00002-of-00004.safetensors | 3 + model-00003-of-00004.safetensors | 3 + model-00004-of-00004.safetensors | 3 + model.safetensors.index.json | 298 + original_adapter/README.md | 202 + original_adapter/adapter_config.json | 32 + original_adapter/adapter_model.safetensors | 3 + special_tokens_map.json | 30 + tokenizer.json | 3 + tokenizer.model | 3 + tokenizer_config.json | 8268 ++++++++++++++++++++ 18 files changed, 9223 insertions(+) create mode 100644 .gitattributes create mode 100644 LICENSE create mode 100644 README.md create mode 100644 config.json create mode 100644 configuration.json create mode 100644 generation_config.json create mode 100644 model-00001-of-00004.safetensors create mode 100644 model-00002-of-00004.safetensors create mode 100644 model-00003-of-00004.safetensors create mode 100644 model-00004-of-00004.safetensors create mode 100644 model.safetensors.index.json create mode 100644 original_adapter/README.md create mode 100644 original_adapter/adapter_config.json create mode 100644 original_adapter/adapter_model.safetensors create mode 100644 special_tokens_map.json create mode 100644 tokenizer.json create mode 100644 tokenizer.model create mode 100644 tokenizer_config.json diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..968676e --- /dev/null +++ b/.gitattributes @@ -0,0 +1,55 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bin.* filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text + +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text + +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zstandard filter=lfs diff=lfs merge=lfs -text +*.tfevents* filter=lfs diff=lfs merge=lfs -text +*.db* filter=lfs diff=lfs merge=lfs -text +*.ark* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*data* filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.meta filter=lfs diff=lfs merge=lfs -text +**/*ckpt*.index filter=lfs diff=lfs merge=lfs -text + +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.gguf* filter=lfs diff=lfs merge=lfs -text +*.ggml filter=lfs diff=lfs merge=lfs -text +*.llamafile* filter=lfs diff=lfs merge=lfs -text +*.pt2 filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text + +model-00004-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text +tokenizer.json filter=lfs diff=lfs merge=lfs -text +model-00001-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text +tokenizer.model filter=lfs diff=lfs merge=lfs -text +model-00003-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text +original_adapter/adapter_model.safetensors filter=lfs diff=lfs merge=lfs -text +model-00002-of-00004.safetensors filter=lfs diff=lfs merge=lfs -text \ No newline at end of file diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..20f500a --- /dev/null +++ b/LICENSE @@ -0,0 +1,97 @@ +Лицензионное соглашение yandexgpt-5-8b-lite + + +Настоящее лицензионное соглашение («Соглашение») распространяется на любое физическое или юридическое лицо («Вы», «Ваш» или «Лицензиат»), которое использует или распространяет Материалы или Производные произведения или любую из их частей. Термины, указанные с заглавной буквы и не имеющие определения, приведены в разделе XI Соглашения. + +Данное Соглашение предоставляет право использования Моделей в Исследовательских или иных Некоммерческих целях с учетом положения в п. I.d Соглашения. + +Используя или распространяя Материалы или Производные произведения или любые из их частей, Вы соглашаетесь с тем, что ознакомились, поняли и обязуетесь соблюдать условия Соглашения. Если Вы не согласны с условиями Соглашения, то Вы не вправе использовать или распространять Материалы или Производные произведения и должны немедленно прекратить использование Материалов и/или Производных произведений. + +Если Вы действуете от имени юридического лица (компании-работодателя или иной организации), то “Вы”, “Ваш” или “Лицензиат” включает вас и такое юридическое лицо, и Вы соглашаетесь с тем, что Вы: (i) являетесь уполномоченным представителем юридического лица, наделенным полномочиями заключить Соглашение от имени такого юридического лица и (ii) принимаете условия Соглашения от имени такого юридического лица. Если у Вас нет необходимых полномочий, Вы не имеете права заключать Соглашение и получать доступ к Материалам от имени такого юридического лица. + +I. УСЛОВИЯ ЛИЦЕНЗИИ + +a. В соответствии с условиями Соглашения Яндекс предоставляет Вам неисключительную, всемирную, непередаваемую, не подлежащую сублицензированию, отзывную и безвозмездную лицензию в отношении права использования Материалов способами воспроизведения, распространения, переработки и создания Производных произведений в Исследовательских или Некоммерческих целях. + +b. Вышеуказанная лицензия является персональной, и Вы не имеете права переуступать или сублицензировать эту лицензию или любые другие права или обязательства по Соглашению без предварительного письменного согласия Яндекса; любая такая переуступка или сублицензия будет недействительной и автоматически и немедленно приведет к прекращению действия Соглашения. + +c. Никакие другие лицензии или права не предоставляются Вам по Соглашению, за исключением прямо указанных в разделе I. Яндекс и его лицензиары оставляют за собой все права, прямо не предоставленные Вам Соглашением. + +d. Для использования Материалов на иных условиях, отличающихся от условий лицензии в настоящем разделе I и Соглашении, необходимо обратиться в Яндекс по следующему адресу cloud-sales@yandex-team.ru. + + +II. ОГРАНИЧЕНИЯ + +Вы не имеете права сами, а также не имеете права разрешать или содействовать третьим лицам в совершении следующих действий: + +a. использовать Материалы или Производные произведения таким образом, что это приводит или может привести к получению, созданию или распространению следующей информации или материалов: + + • незаконная и/или запрещенная для распространения информация; + • информация, содержащая советы по обходу закона, инструкции и указания по способам нарушения прав третьих лиц; + • неэтичная или оскорбительная для отдельных лиц или категорий лиц информация; + • информация, разжигающая межнациональную рознь, пропагандирующая ненависть и/или дискриминацию людей по расовому, этническому, половому, религиозному, социальному и иным признакам, порочащая честь, достоинство и/или деловую репутацию третьих лиц; + • порнографические материалы, в том числе, с участием несовершеннолетних; + • информация, нарушающая права на частную жизнь, содержащая персональные данные лиц, а также иная информация ограниченного доступа, включая коммерческую, банковскую, налоговую, семейную медицинскую тайну, тайну корреспонденции и т.д.; + • информация, нарушающая авторские права, права на товарные знаки, средства индивидуализации и/или права на иные объекты интеллектуальной собственности, принадлежащие третьим лицам. + +b. изменять или удалять уведомления об авторских правах и других правах собственности, содержащихся в Материалах; + +c. использовать любое оборудование, устройства, программное обеспечение или другие средства для обхода или устранения любых средств защиты, используемых Яндексом в отношении Моделей, или для обхода или устранения любых ограничений на их использование, или для включения функций Моделей, отключенных Яндексом; или + +d. предлагать или навязывать какие-либо условия в отношении Материалов, которые изменяют, ограничивают или несовместимы с условиями Соглашения. + + +III. УКАЗАНИЕ АВТОРСТВА + +При распространении Материалов, а также их Производных произведений, или произведений, включающих Материалы) Вы должны (i) предоставить копию Соглашения и (ii) указать следующее уведомление об авторских правах: “YandexGPT-5-Lite-8B-pretrain распространяется на условиях Лицензионного соглашения YandexGPT-5-Lite-8B-pretrain. Copyright (c) 2025, ООО «ЯНДЕКС». Все права защищены”. + +IV. ОТКАЗ ОТ ОТВЕТСТВЕННОСТИ + +МАТЕРИАЛЫ ПРЕДОСТАВЛЯЮТСЯ “КАК ЕСТЬ” и “СО ВСЕМИ ИСПРАВЛЕНИЯМИ” БЕЗ КАКИХ-ЛИБО ГАРАНТИЙ, ЯВНЫХ ИЛИ ПОДРАЗУМЕВАЕМЫХ. ЯНДЕКС КАТЕГОРИЧЕСКИ ОТКАЗЫВАЕТСЯ ОТ ВСЕХ ЗАЯВЛЕНИЙ И ГАРАНТИЙ, ЯВНЫХ ИЛИ ПОДРАЗУМЕВАЕМЫХ, БУДЬ ТО В СИЛУ ЗАКОНА, ОБЫЧАЕВ, ИСПОЛЬЗОВАНИЯ ИЛИ ИНЫМ ОБРАЗОМ, В ОТНОШЕНИИ ЛЮБЫХ ВОПРОСОВ, СВЯЗАННЫХ С МАТЕРИАЛАМИ, ВКЛЮЧАЯ, НО НЕ ОГРАНИЧИВАЯСЬ, ПОДРАЗУМЕВАЕМЫЕ ГАРАНТИИ ТОВАРНОЙ ПРИГОДНОСТИ, ПРИГОДНОСТИ ДЛЯ ОПРЕДЕЛЕННОЙ ЦЕЛИ, ПРАВА СОБСТВЕННОСТИ, КАЧЕСТВА ИЛИ НЕНАРУШЕНИЯ ПРАВ. ЯНДЕКС НЕ ДАЕТ НИКАКИХ ГАРАНТИЙ ИЛИ ЗАВЕРЕНИЙ В ТОМ, ЧТО МАТЕРИАЛЫ НЕ СОДЕРЖАТ ОШИБОК, ВИРУСОВ ИЛИ ДРУГИХ ВРЕДОНОСНЫХ КОМПОНЕНТОВ И ЧТО ИСПОЛЬЗОВАНИЕ МАТЕРИАЛОВ ПРИВОДИТ К КАКИМ-ЛИБО КОНКРЕТНЫМ РЕЗУЛЬТАТАМ. + +V. ОГРАНИЧЕНИЕ ОТВЕТСТВЕННОСТИ + +ЯНДЕКС НИ ПРИ КАКИХ ОБСТОЯТЕЛЬСТВАХ НЕ НЕСЕТ ОТВЕТСТВЕННОСТИ ПЕРЕД ВАМИ (А) ЗА ЛЮБЫЕ УБЫТКИ И ПОСЛЕДСТВИЯ ИСПОЛЬЗОВАНИЯ МАТЕРИАЛОВ В СООТВЕТСТВИИ ИЛИ В НАРУШЕНИЕ УСЛОВИЙ СОГЛАШЕНИЯ, ИЛИ (Б) ЗА ЛЮБЫЕ КОСВЕННЫЕ, СЛУЧАЙНЫЕ, ШТРАФНЫЕ ИЛИ СПЕЦИАЛЬНЫЕ УБЫТКИ, ВКЛЮЧАЯ УПУЩЕННУЮ ВЫГОДУ, ДАЖЕ ЕСЛИ ЯНДЕКСУ БЫЛо ИЗВЕСТНО О ВОЗМОЖНОСТИ ТАКИХ УБЫТКОВ. МАТЕРИАЛЫ, ИХ СОСТАВНЫЕ ЭЛЕМЕНТЫ И ЛЮБЫЕ ВЫХОДНЫЕ ДАННЫЕ ИЗ ТАКИХ МАТЕРИАЛОВ НЕ РАЗРАБОТАНЫ И НЕ ПРЕДНАЗНАЧЕНЫ ДЛЯ ИСПОЛЬЗОВАНИЯ В КАКИХ-ЛИБО ПРИЛОЖЕНИЯХ ИЛИ СИТУАЦИЯХ, КОГДА МОЖНО ОБОСНОВАННО ПРЕДПОЛОЖИТЬ, ЧТО НЕКОРРЕКТНАЯ РАБОТА МАТЕРИАЛОВ, СБОЙ В НИХ МОЖЕТ ПРИВЕСТИ К ТРАВМАМ ИЛИ НАРУШЕНИЮ ПРАВ ЧЕЛОВЕКА. + +VI. ВОЗМЕЩЕНИЕ УБЫТКОВ + +Вы обязуетесь защитить Яндекс и Аффилированных лиц и выступить на стороне Яндекс или Аффилированных лиц при предъявлении Яндексу или Аффилированным лицам претензий, требований, судебных исков третьими лицами («Претензии»), вытекающих из или связанных с использованием Вами Материалов (а также любых результатов или данных, полученные вследствие использования Материалов), а также всячески содействовать в урегулировании таких Претензий. Вы обязуетесь возместить Яндексу или Аффилированным лицам реальный документально подтвержденный ущерб, возникший в связи с Претензиями. + +VII. ПРЕКРАЩЕНИЕ ДЕЙСТВИЯ СОГЛАШЕНИЯ + + a. Действие Соглашения автоматически прекращается при любом нарушении Вами условий Соглашения. + b. Яндекс может прекратить действие Соглашения, полностью или частично, в любое время, направив Вам уведомление (в том числе в электронном виде). + c. Следующие разделы Соглашения остаются в силе даже после прекращения его действия: II (ОГРАНИЧЕНИЯ), III (УКАЗАНИЕ АВТОРСТВА), IV (ОТКАЗ ОТ ОТВЕТСТВЕННОСТИ), V (ОГРАНИЧЕНИЕ ОТВЕТСТВЕННОСТИ), VI (ВОЗМЕЩЕНИЕ УБЫТКОВ), VII (ПРЕКРАЩЕНИЕ ДЕЙСТВИЯ СОГЛАШЕНИЯ), VIII (ТОВАРНЫЕ ЗНАКИ), IX (ПРИМЕНИМОЕ ПРАВО; РАЗРЕШЕНИЕ СПОРОВ) и X (ИНОЕ). + + +VIII. ТОВАРНЫЕ ЗНАКИ И УПОМИНАНИЯ ЯНДЕКСА + +Соглашение не предполагает предоставления Лицензиату лицензии или иного разрешения в отношении права использования товарных знаков Яндекса или иных обозначений Яндекса. Лицензиат не вправе использовать какое-либо наименование или товарные знаки Яндекса без предварительного письменного согласия Яндекса, за исключением случаев, когда это необходимо для указания уведомления об авторских правах, требуемого разделом III “УКАЗАНИЕ АВТОРСТВА” Соглашения. + +IX. ПРИМЕНИМОЕ ПРАВО; ПОРЯДОК РАЗРЕШЕНИЯ СПОРОВ + +Соглашение регулируется и толкуется в соответствии с законодательством Российской Федерации. Любой иск или разбирательство, вытекающие из Соглашения или связанные с ним, должны рассматриваться в судах г. Москвы, и каждая сторона безоговорочно подчиняется юрисдикции и месту проведения таких судов. + +X. ИНОЕ + +Если какое-либо положение или часть положения Соглашения признается незаконным, недействительным или не имеющим законной силы, такое положение или его часть считаются исключенными из Соглашения и не влияют на действительность и применимость остальных положений Соглашения. Нереализация Яндексом какого-либо права или положения Соглашения не будет считаться отказом от такого права или положения. Соглашение вместе с Документацией образует единое соглашение между вами и Яндексом относительно предмета Соглашения и заменяет собой все иные письменные или устные соглашения и договоренности относительно такого предмета. Никакие изменения или дополнения к каким-либо положениям Соглашения не будут иметь обязательной силы, если они не оформлены в письменной форме и не подписаны уполномоченными представителями от Вас и Яндекса. + +XI. ТЕРМИНЫ  + +«Аффилированные лица» – любые юридические или физические лица, которые имеют прямой или косвенный контроль над Яндексом; над которыми Яндекс имеет прямой или косвенный контроль; либо которые находятся с Яндексом под общим прямым или косвенным контролем. + +«Соглашение» – настоящее лицензионное соглашение YandexGPT-5-Lite-8B-pretrain License Agreement. + +«Производные произведения» - (a) любые производные от Материалов работы в значении, предусмотренном Гражданским Кодексом Российской Федерации и (b) любые модификации Модели и любые другие модели, созданные на основе Модели или производные от нее или выходных данных Модели. + +“Документация” - любые спецификации, руководства, документы и иная письменная информация, предоставляемая Яндексом в отношении Моделей. + +“Материалы” – совместно Модели и Документация (любая их часть или комбинация), принадлежащие Яндексу и предоставляемые по лицензии в рамках Соглашения.  + +“Модели" – в совокупности собственные модели и алгоритмы Яндекса, включая модели машинного обучения, весовые коэффициенты обученных моделей (основные параметры обученной модели машинного обучения, которые определяют, как модель делает предсказание следующего токена), программное обеспечение и другие элементы вышеперечисленного, которые предоставляются по лицензии в рамках Соглашения. + +“Некоммерческие цели” - любая цель, отличная от исследовательской, которая не направлена на получение коммерческой выгоды или денежной компенсации Вами или другими лицами, например, для личного использования или для оценки и тестирования.   + +“Исследовательские цели” – цели академического или научного развития, не направленные на получение коммерческой выгоды или денежной компенсации Вами или другими лицами. + +"Яндекс" – ООО «ЯНДЕКС» и его Аффилированные лица. \ No newline at end of file diff --git a/README.md b/README.md new file mode 100644 index 0000000..7a08255 --- /dev/null +++ b/README.md @@ -0,0 +1,183 @@ +--- +library_name: transformers +model_name: Vikhrmodels/Vikhr-YandexGPT-5-Lite-8B-it +datasets: +- Vikhrmodels/GrandMaster-PRO-MAX +- Vikhrmodels/Grounded-RAG-RU-v2 +base_model: +- yandex/YandexGPT-5-Lite-8B-pretrain +language: +- ru +- en +license: other +license_name: yandexgpt-5-lite-8b-pretrain +license_link: LICENSE +--- + +# Vikhr-YandexGPT-5-Lite-8B-it + +Инструктивная модель на основе **YandexGPT-5-Lite-8B-pretrain**, обученная на русскоязычном датасете **GrandMaster-PRO-MAX** и **Grounded-RAG-RU-v2** с использованием **SFT**. + + +## Quatized variants: + - [GGUF](https://hf.co/Vikhrmodels/Vikhr-YandexGPT-5-Lite-8B-it_GGUF) + - MLX + - [4 bit](https://hf.co/Vikhrmodels/Vikhr-YandexGPT-5-Lite-8B-it_MLX-4bit) + - [8 bit](https://hf.co/Vikhrmodels/Vikhr-YandexGPT-5-Lite-8B-it_MLX-8bit) + + +## Особенности: + +- 📚 Основа: [YandexGPT-5-Lite-8B-pretrain](https://huggingface.co/yandex/YandexGPT-5-Lite-8B-pretrain) +- 💾 Датасет / Dataset: [GrandMaster-PRO-MAX](https://huggingface.co/datasets/Vikhrmodels/GrandMaster-PRO-MAX), [Grounded-RAG-RU-v2](https://huggingface.co/datasets/Vikhrmodels/Grounded-RAG-RU-v2) +- 🇷🇺 Специализация: **RU** +- 🌍 Поддержка: **Bilingual RU/EN** + +## Попробовать / Try now: + +[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1jIm0beQiUoW6bn57jixEdFEgIa-vZMLM?usp=sharing) + + +## Обучение: + +**Vikhr-YandexGPT-5-Lite-8B-it** была создана с использованием метода SFT (Supervised Fine-Tuning). + +#### Инструктивная SFT часть + +Для SFT этапа обучения модели мы подготовили большой (150к инструкций) инструктивный синтетический датасет [Vikhrmodels/GrandMaster-PRO-MAX](https://huggingface.co/datasets/Vikhrmodels/GrandMaster-PRO-MAX). Его особенностью является встроеный CoT (Chain-Of-Thought), для сбора которого мы использовали модифицированный промет для gpt-4-turbo, подробности в карточке датасета. + +Кроме того, для того чтобы сделать RAG Grounding, мы подготовили другой синтетический датасет - [Vikhrmodels/Grounded-RAG-RU-v2](https://huggingface.co/datasets/Vikhrmodels/Grounded-RAG-RU-v2) (50k диалогов), его пайплайн сборки достаточно сложный для короткого описания и полробнее об этом вы можете прочитать в его карточке. + +[Конфиг обучения](https://github.com/VikhrModels/effective_llm_alignment/tree/main/training_configs/sft/sft-yandex-lora-GrandmasterRAG.yaml) + +## Пример кода для запуска: + +```python +from transformers import AutoModelForCausalLM, AutoTokenizer + +# Load the model and tokenizer +model_name = "Vikhrmodels/Vikhr-YandexGPT-5-Lite-8B-it" +model = AutoModelForCausalLM.from_pretrained(model_name) +tokenizer = AutoTokenizer.from_pretrained(model_name) + +# Prepare the input text +input_text = "Напиши краткое описание фильма Назад в будущее." + +messages = [ + {"role": "user", "content": input_text}, +] + +# Tokenize and generate text +input_ids = tokenizer.apply_chat_template(messages, truncation=True, add_generation_prompt=True, return_tensors="pt") +output = model.generate( + input_ids, + max_length=1512, + temperature=0.7, +) + +# Decode and print result +generated_text = tokenizer.decode(output[0], skip_special_tokens=True) +print(generated_text) +``` + +#### Ответ модели: + +>"Назад в будущее" (англ. "Back to the Future") — это американский научно-фантастический фильм, выпущенный в 1985 году. Режиссёром картины выступил Роберт Земекис, а сценарий написал Боб Гейл. Главные роли исполнили Майкл Дж. Фокс, Кристофер Ллойд и Лиа Томпсон. +> +>Фильм рассказывает историю Марти МакФлая, обычного подростка из 1985 года, который случайно попадает в 1955 год благодаря изобретению своего друга-ученого, доктора Эмметта Брауна. Марти оказывается в прошлом, где он должен помочь доктору Брауну, который в то время был молодым и наивным, изобрести машину времени. +> +>В процессе своих приключений Марти встречает молодого доктора Брауна и его семью, а также влюбляется в девушку, которая в будущем станет его матерью. Марти должен не только исправить ошибки прошлого, но и предотвратить катастрофу, которая может изменить будущее. +> +>Фильм получил множество наград и стал культовым, породив два сиквела и множество мемов и цитат, которые до сих пор популярны. + +### Как работать с RAG + +Роль documents представляет из себя список словарей с описанием контента документов, с примнением `json.dumps(array, ensure_ascii=False)` (см. пример ниже). \ +Контент документов может быть представлен в **3** различных форматах: **Markdown**, **HTML**, **Plain Text**. Контент каждого документа - может быть чанком текста длиной до 4к символов. + +```json +[ + { + "doc_id": (0..5), + "title": "(null or str)", + "content": "(html or markdown or plain text)" + } +] +``` + +#### Пример правильного использования с OpenAI-like API + +Запуск vLLM сервера: `vllm serve --dtype half --max-model-len 32000 -tp 1 Vikhrmodels/Vikhr-YandexGPT-5-Lite-8B-it --api-key token-abc123` + +```python +GROUNDED_SYSTEM_PROMPT = "Your task is to answer the user's questions using only the information from the provided documents. Give two answers to each question: one with a list of relevant document identifiers and the second with the answer to the question itself, using documents with these identifiers." +documents = [ + { + "doc_id": 0, + "title": "Глобальное потепление: ледники", + "content": "За последние 50 лет объем ледников в мире уменьшился на 30%" + }, + { + "doc_id": 1, + "title": "Глобальное потепление: Уровень моря", + "content": "Уровень мирового океана повысился на 20 см с 1880 года и продолжает расти на 3,3 мм в год" + } +] +sample_history = [ + {'role': 'system', 'content': GROUNDED_SYSTEM_PROMPT}, + {'role': 'documents', 'content': json.dumps(documents, ensure_ascii=False)}, + {'role': 'user', 'content': 'Глоабльное потепление'} +] +relevant_indexes = llm_client.chat.completions.create( + model=llm_model, + messages=sample_history, + temperature=0.0, + max_tokens=2048 +).choices[0].message.content +print('Using documents: ' + relevant_indexes + '\n----') +final_answer = llm_client.chat.completions.create( + model=llm_model, + messages=sample_history + [{'role': 'assistant', 'content': relevant_indexes}], + temperature=0.3, + max_tokens=2048 +).choices[0].message.content +print(final_answer) +``` + +Ответ после выполнения кода будет выглядеть примерно так: + +>Using documents: {"relevant_doc_ids": [0, 1]} +>---- +>Глобальное потепление – это долгосрочное повышение средней температуры атмосферы и океанов Земли. Это явление имеет множество последствий для нашей планеты, и среди них можно выделить два ключевых аспекта, основанных на доступных мне данных: +> +>1. **Уменьшение объема ледников**: За последние 50 лет наблюдается значительное сокращение объема ледников по всему миру. Согласно данным, объем ледников уменьшился на 30%. Это может быть связано с таянием ледников из-за повышения температур, что является одним из признаков глобального потепления. +> +>2. **Повышение уровня моря**: Уровень мирового океана также увеличивается, что связано с таянием ледников и ледяных покровов, а также с расширением воды при повышении температуры. С 1880 года уровень моря повысился на 20 сантиметров, и этот процесс продолжается, с ежегодным увеличением на 3,3 миллиметра. +> +>Эти изменения имеют серьезные последствия для экосистем, климата и человеческого общества. Таяние ледников приводит к повышению уровня моря, что может привести к затоплению прибрежных территорий и островов, а также к изменению водных ресурсов и климатических паттернов. + +Используя первый ответ модели `relevant_indexes` (JSON), можно понять нашла ли модель информацию в документах или нет, она обучена возврашать пустой массив если ее нет и в таком случае она будет отвечать, что не смогла найти информацию в базе знаний (при генерации второго ответа). + +### Нюансы и ограничения +- Модель имеет **низкий уровень безопасности ответов** и нацелена на правильное и полное выполенние инструкций, имейте это ввиду при использовании и тестируйте самостоятельно. Частично это исправляется системными промптами и дополнительными указаниями о важности безопасности в промпте пользователя. +- Системные промпты не предназначены для описание персонажей, мы рекомендуем использовать их для спецификации стиля ответа (вроде "answer only in json format"). Кроме того, желательно, писать их **на английском языке**, так как так было в датасете, от использования английского в системных промтпах не зависит язык ответа. +- RAG режим **требует обязательного** наличия системного промпта `GROUNDED_SYSTEM_PROMPT` описаного в секции *Как работать с RAG*. Так же иногда модель может добавлять общую информацию из своих знаний в ответ к той, что есть в документах. +- Модель лучше использовать с низкой темптературой (0.1-0.5), а таже использовать top_k (30-50), при температуре 1.0 были замечены случайные дефекты генерации. + +### Авторы + +- Sergei Bratchikov, [NLP Wanderer](https://t.me/nlpwanderer), [Vikhr Team](https://t.me/vikhrlabs) +- Nikolay Kompanets, [LakoMoor](https://t.me/lakomoordev), [Vikhr Team](https://t.me/vikhrlabs) +- Konstantin Korolev, [Vikhr Team](https://t.me/vikhrlabs) +- Aleksandr Nikolich, [Vikhr Team](https://t.me/vikhrlabs) + +``` +@inproceedings{nikolich2024vikhr, + title={Vikhr: Advancing Open-Source Bilingual Instruction-Following Large Language Models for Russian and English}, + author={Aleksandr Nikolich and Konstantin Korolev and Sergei Bratchikov and Nikolay Kompanets and Igor Kiselev and Artem Shelmanov}, + booktitle={Proceedings of the 4th Workshop on Multilingual Representation Learning (MRL) @ EMNLP-2024}, + year={2024}, + publisher={Association for Computational Linguistics}, + url={https://arxiv.org/pdf/2405.13929} +} +``` \ No newline at end of file diff --git a/config.json b/config.json new file mode 100644 index 0000000..edd8cf6 --- /dev/null +++ b/config.json @@ -0,0 +1,30 @@ +{ + "_name_or_path": "yandex/YandexGPT-5-Lite-8B-pretrain", + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 1, + "eos_token_id": 2, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 4096, + "initializer_range": 0.02, + "intermediate_size": 14336, + "max_position_embeddings": 32768, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 32, + "num_hidden_layers": 32, + "num_key_value_heads": 8, + "pretraining_tp": 1, + "rms_norm_eps": 1e-06, + "rope_scaling": null, + "rope_theta": 500000.0, + "tie_word_embeddings": false, + "torch_dtype": "bfloat16", + "transformers_version": "4.49.0", + "use_cache": 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a/original_adapter/README.md b/original_adapter/README.md new file mode 100644 index 0000000..4f98cda --- /dev/null +++ b/original_adapter/README.md @@ -0,0 +1,202 @@ +--- +base_model: yandex/YandexGPT-5-Lite-8B-pretrain +library_name: peft +--- + +# Model Card for Model ID + + + + + +## Model Details + +### Model Description + + + + + +- **Developed by:** [More Information Needed] +- **Funded by [optional]:** [More Information Needed] +- **Shared by [optional]:** [More Information Needed] +- **Model type:** [More Information Needed] +- **Language(s) (NLP):** [More Information Needed] +- **License:** [More Information Needed] +- **Finetuned from model [optional]:** [More Information Needed] + +### Model Sources [optional] + + + +- **Repository:** [More Information Needed] +- **Paper [optional]:** [More Information Needed] +- **Demo [optional]:** [More Information Needed] + +## Uses + + + +### Direct Use + + + +[More Information Needed] + +### Downstream Use [optional] + + + +[More Information Needed] + +### Out-of-Scope Use + + + +[More Information Needed] + +## Bias, Risks, and Limitations + + + +[More Information Needed] + +### Recommendations + + + +Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. + +## How to Get Started with the Model + +Use the code below to get started with the model. + +[More Information Needed] + +## Training Details + +### Training Data + + + +[More Information Needed] + +### Training Procedure + + + +#### Preprocessing [optional] + +[More Information Needed] + + +#### Training Hyperparameters + +- **Training regime:** [More Information Needed] + +#### Speeds, Sizes, Times [optional] + + + +[More Information Needed] + +## Evaluation + + + +### Testing Data, Factors & Metrics + +#### Testing Data + + + +[More Information Needed] + +#### Factors + + + +[More Information Needed] + +#### Metrics + + + +[More Information Needed] + +### Results + +[More Information Needed] + +#### Summary + + + +## Model Examination [optional] + + + +[More Information Needed] + +## Environmental Impact + + + +Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). + +- **Hardware Type:** [More Information Needed] +- **Hours used:** [More Information Needed] +- **Cloud Provider:** [More Information Needed] +- **Compute Region:** [More Information Needed] +- **Carbon Emitted:** [More Information Needed] + +## Technical Specifications [optional] + +### Model Architecture and Objective + +[More Information Needed] + +### Compute Infrastructure + +[More Information Needed] + +#### Hardware + +[More Information Needed] + +#### Software + +[More Information Needed] + +## Citation [optional] + + + +**BibTeX:** + +[More Information Needed] + +**APA:** + +[More Information Needed] + +## Glossary [optional] + + + +[More Information Needed] + +## More Information [optional] + +[More Information Needed] + +## Model Card Authors [optional] + +[More Information Needed] + +## Model Card Contact + +[More Information Needed] +### Framework versions + +- PEFT 0.12.0 \ No newline at end of file diff --git a/original_adapter/adapter_config.json b/original_adapter/adapter_config.json new file mode 100644 index 0000000..36f1e78 --- /dev/null +++ b/original_adapter/adapter_config.json @@ -0,0 +1,32 @@ +{ + "alpha_pattern": {}, + "auto_mapping": null, + "base_model_name_or_path": "yandex/YandexGPT-5-Lite-8B-pretrain", + "bias": "none", + "fan_in_fan_out": false, + "inference_mode": true, + "init_lora_weights": true, + "layer_replication": null, + "layers_pattern": null, + "layers_to_transform": null, + "loftq_config": {}, + "lora_alpha": 256, + "lora_dropout": 0.05, + "megatron_config": null, + "megatron_core": "megatron.core", + "modules_to_save": null, + "peft_type": "LORA", + "r": 256, + "rank_pattern": {}, + "revision": null, + "target_modules": [ + "qkv_proj", + "lm_head", + "o_proj", + "gate_up_proj", + "down_proj" + ], + "task_type": "CAUSAL_LM", + "use_dora": false, + "use_rslora": false +} \ No newline at end of file diff --git a/original_adapter/adapter_model.safetensors 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"rstrip": false, + "single_word": false, + "special": false + }, + "128978": { + "content": "[SPEC_TOKEN_978]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128979": { + "content": "[SPEC_TOKEN_979]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128980": { + "content": "[SPEC_TOKEN_980]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128981": { + "content": "[SPEC_TOKEN_981]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128982": { + "content": "[SPEC_TOKEN_982]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128983": { + "content": "[SPEC_TOKEN_983]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, 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false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128991": { + "content": "[SPEC_TOKEN_991]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128992": { + "content": "[SPEC_TOKEN_992]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128993": { + "content": "[SPEC_TOKEN_993]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128994": { + "content": "[SPEC_TOKEN_994]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128995": { + "content": "[SPEC_TOKEN_995]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128996": { + "content": "[SPEC_TOKEN_996]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128997": { + "content": "[SPEC_TOKEN_997]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128998": { + "content": "[SPEC_TOKEN_998]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "128999": { + "content": "[SPEC_TOKEN_999]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129000": { + "content": "[SPEC_TOKEN_1000]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129001": { + "content": "[SPEC_TOKEN_1001]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": true + }, + "129002": { + "content": "[SPEC_TOKEN_1002]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129003": { + "content": "[SPEC_TOKEN_1003]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129004": { + "content": "[SPEC_TOKEN_1004]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129005": { + "content": "[SPEC_TOKEN_1005]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129006": { + "content": "[SPEC_TOKEN_1006]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129007": { + "content": "[SPEC_TOKEN_1007]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129008": { + "content": "[SPEC_TOKEN_1008]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129009": { + "content": "[SPEC_TOKEN_1009]", + "lstrip": false, + 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false, + "special": false + }, + "129016": { + "content": "[SPEC_TOKEN_1016]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129017": { + "content": "[SPEC_TOKEN_1017]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129018": { + "content": "[SPEC_TOKEN_1018]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129019": { + "content": "[SPEC_TOKEN_1019]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129020": { + "content": "[SPEC_TOKEN_1020]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129021": { + "content": "[SPEC_TOKEN_1021]", + "lstrip": false, + "normalized": false, + "rstrip": false, + "single_word": false, + "special": false + }, + "129022": { + "content": 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