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Model: TsitkoD/Qwen3-14B-Vedun-v5-bf16 Source: Original Platform
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README.md
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---
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license: apache-2.0
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language:
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- ru
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base_model: Qwen/Qwen3-14B
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library_name: mlx
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pipeline_tag: text-generation
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tags:
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- mlx
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- qwen3
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- lora
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- russian
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- vedun
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- buktitsa
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- slavic
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- entertainment
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- creative-writing
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datasets:
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- TsitkoD/vedun-lora-data
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---
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<p align="center">
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<img src="cover.jpg" alt="Vedun" width="480"/>
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</p>
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# 🪶 Qwen3-14B-Vedun-v5 — *bf16 — без квантизации*
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> *«А что если спросить старого ведуна, что такое “правда”? Он не ответит цитатой
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> из Даля — он разберёт слово на буквы, расскажет образ каждой, найдёт лор в
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> Велесовой Книге и свернёт это обратно в формулировку.»*
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Это и делает **Vedun** — LoRA-дообучение `Qwen/Qwen3-14B` на синтетическом
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датасете [`TsitkoD/vedun-lora-data`](https://huggingface.co/datasets/TsitkoD/vedun-lora-data). Модель
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отвечает на русскоязычные вопросы через структурный разбор по **Древнеславянской
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Буквице**:
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```
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[Буквицы:] — что значит каждая буква (имя, числовое значение, образ)
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[Образ:] — как из значений букв собирается смысл слова
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[Лор:] — отсылки к Велесовой Книге и буквичной традиции
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[Формулировка:] — финальная свёртка
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```
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На «житейских» вопросах (вроде *«как простить предательство?»*) модель сначала
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вытаскивает 2–4 ключевых слова и разбирает **каждое отдельно** через Буквицу,
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а потом склеивает ответ.
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> ⚠️ **Дисклеймер.** Это развлекательный pet-project, а не пророчества, религия
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> или философия. Результаты модели — стилизованный текст в эстетике
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> «древнеславянской буквицы» по мотивам соответствующих источников. Относитесь
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> к этому с юмором, не используйте как руководство к действию, духовную практику
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> или жизненные правила.
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## ✨ Что получишь на выходе
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**Q: Как простить предательство?**
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> Простить предательство — это не забыть, а **восстановить гармонию между
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> Явью и Навью**. Буквица «простить» говорит нам: через осознание (Слово)
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> и утверждение (Твердо) мы возвращаемся к равновесию (Иже)…
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**Q: В чём смысл жизни?**
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> Смысл жизни — это не абстрактная философия, а **Вопрос, который ведёт нас
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> к Веди** через созерцание и гармонию. Жизнь — это «Наше» сотворённое на
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> Земле, где мы ищем основу (Оно) в потоке Рока…
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**Q: Что такое «правда»?**
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> По Буквице «правда» — П-Р-А-В-Д-А = Покои-Реци-Азъ-Веди-Добро-Азъ.
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> «Покой созерцания, изречённый Творцом, познанный Добром и утверждённый
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> Изначальным»…
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(Это реальные ответы модели — не cherry-pick из тысячи попыток.)
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## 🚀 Быстрый старт
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### LM Studio (самый простой способ)
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1. Скачай из HF в LM Studio: вставь `TsitkoD/Qwen3-14B-Vedun-v5-bf16`
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в строку поиска моделей.
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2. Загрузи. Спроси «Что такое правда?». Получи разбор по буквам.
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### Python + MLX
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```python
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from mlx_lm import load, generate
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model, tokenizer = load("TsitkoD/Qwen3-14B-Vedun-v5-bf16")
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prompt = tokenizer.apply_chat_template(
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[{"role": "user", "content": "Что такое «правда»?"}],
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add_generation_prompt=True,
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tokenize=False,
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)
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print(generate(model, tokenizer, prompt=prompt, max_tokens=2000, verbose=False))
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```
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## 📦 Какой вариант выбрать
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| Вариант | Размер | RAM при загрузке | Когда брать |
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|---|---|---|---|
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||||
| [**bf16**](https://huggingface.co/TsitkoD/Qwen3-14B-Vedun-v5-bf16) | ~28 GB | ~30 GB | Эталон. Самый точный буквичный разбор. |
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| [**q8**](https://huggingface.co/TsitkoD/Qwen3-14B-Vedun-v5-q8) | ~15 GB | ~16 GB | Почти не отличается от bf16, экономит память. **Рекомендуется.** |
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||||
| [**q4**](https://huggingface.co/TsitkoD/Qwen3-14B-Vedun-v5-q4) | ~7.8 GB | ~9 GB | Запускается на 16 GB ноутбуке. Иногда теряет буквы. |
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Все три варианта обучены **одинаково** — отличие только в квантизации весов
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после обучения.
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## 🛠 Как обучали
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Цепочка из трёх стадий LoRA-дообучения на Mac Studio M4 Max 128 GB,
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||||
фреймворк [`mlx_lm`](https://github.com/ml-explore/mlx-examples) +
|
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кастомный `train_lora_weighted.py`:
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| Стадия | Итер | max_seq | Особенность |
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|---|---|---|---|
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| **v3_14b** (с нуля) | 1000 | 2048 | Базовое обучение на корпусе разборов |
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| **v4_14b** (resume v3) | 600 | 2048 | + `letter_weight=5.0` — CE-loss на токенах блока `[Буквицы:]` × 5 |
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| **v5_14b** (resume v4) | 1000 | 3072 | + multi-term датасет (житейские вопросы) |
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Параметры LoRA: `rank=8, scale=20, dropout=0, num_layers=40`, AdamW, lr=3e-5,
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`batch=1 × grad_accum=4`, gradient checkpointing.
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**Финальный val loss: 0.694** (против 0.784 у 4B-версии — на тех же данных).
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## 📊 Eval
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На небольшом контрольном наборе (`bf16`-вариант):
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| Метрика | Результат |
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||||
|---|---|
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||||
| Совпадение букв в `[Буквицы:]` (7 коротких терминов) | **7/7** |
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| Полнота структуры разбора | **7/7** |
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| Multi-term структура (3 житейских вопроса) | **3/3** |
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||||
| Среднее число sub-блоков на житейский вопрос | **3.0** |
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||||
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## ⚠️ Ограничения и честные оговорки
|
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||||
- Это **стилизация** в эстетике буквицы, а не источник лингвистической истины.
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Модель уверенно выдаёт реконструированные значения букв, многие из которых
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не имеют академического подтверждения.
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- На вопросах вне славянско-буквичного домена модель всё равно будет пытаться
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разобрать слово через Буквицу — это by design, но иногда выглядит комично.
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- Квантизованные варианты (q4 особенно) могут терять/путать буквы в разборе.
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Если важна точность букв — бери bf16 или q8.
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- Модель умеет в `<think>…</think>` reasoning. Если хочешь только финальный
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ответ — отрежь содержимое тега в постпроцессинге.
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## 🔗 Связанное
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- 📚 Датасет: [`TsitkoD/vedun-lora-data`](https://huggingface.co/datasets/TsitkoD/vedun-lora-data)
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- 🧬 База: [`Qwen/Qwen3-14B`](https://huggingface.co/Qwen/Qwen3-14B)
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- 🌐 Рантайм: [`mlx_lm`](https://github.com/ml-explore/mlx-examples) (Apple Silicon)
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## Лицензия
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Apache 2.0 (как у `Qwen/Qwen3-14B`).
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added_tokens.json
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added_tokens.json
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{
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"</think>": 151668,
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"</tool_call>": 151658,
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"</tool_response>": 151666,
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"<think>": 151667,
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"<tool_call>": 151657,
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"<tool_response>": 151665,
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"<|box_end|>": 151649,
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"<|box_start|>": 151648,
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"<|endoftext|>": 151643,
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"<|file_sep|>": 151664,
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"<|fim_middle|>": 151660,
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"<|fim_pad|>": 151662,
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"<|fim_prefix|>": 151659,
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"<|fim_suffix|>": 151661,
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"<|im_end|>": 151645,
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"<|im_start|>": 151644,
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"<|image_pad|>": 151655,
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"<|object_ref_end|>": 151647,
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"<|object_ref_start|>": 151646,
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"<|quad_end|>": 151651,
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"<|quad_start|>": 151650,
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"<|repo_name|>": 151663,
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"<|video_pad|>": 151656,
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"<|vision_end|>": 151653,
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"<|vision_pad|>": 151654,
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"<|vision_start|>": 151652
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}
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chat_template.jinja
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{{- messages[0].content + '\n\n' }}
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{%- endif %}
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{{- "# 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>" }}
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{%- for tool in tools %}
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||||
{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\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" }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- for message in messages[::-1] %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- if ns.multi_step_tool and message.role == "user" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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{%- endif %}
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||||
{%- endfor %}
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{%- for message in messages %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{%- set content = message.content %}
|
||||
{%- set reasoning_content = '' %}
|
||||
{%- if message.reasoning_content is defined and message.reasoning_content is not none %}
|
||||
{%- set reasoning_content = message.reasoning_content %}
|
||||
{%- else %}
|
||||
{%- if '</think>' in message.content %}
|
||||
{%- set content = message.content.split('</think>')[-1].lstrip('\n') %}
|
||||
{%- set reasoning_content = message.content.split('</think>')[0].rstrip('\n').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 %}
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||||
{{- '}\n</tool_call>' }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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||||
{{- '<|im_start|>user' }}
|
||||
{%- endif %}
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||||
{{- '\n<tool_response>\n' }}
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||||
{{- message.content }}
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||||
{{- '\n</tool_response>' }}
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||||
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
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||||
{%- endif %}
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||||
{%- endfor %}
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||||
{%- if add_generation_prompt %}
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||||
{{- '<|im_start|>assistant\n' }}
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||||
{%- if enable_thinking is defined and enable_thinking is false %}
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||||
{{- '<think>\n\n</think>\n\n' }}
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||||
{%- endif %}
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||||
{%- endif %}
|
||||
30
config.json
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config.json
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{
|
||||
"architectures": [
|
||||
"Qwen3ForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 151643,
|
||||
"eos_token_id": 151645,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 5120,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 17408,
|
||||
"max_position_embeddings": 40960,
|
||||
"max_window_layers": 40,
|
||||
"model_type": "qwen3",
|
||||
"num_attention_heads": 40,
|
||||
"num_hidden_layers": 40,
|
||||
"num_key_value_heads": 8,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_scaling": null,
|
||||
"rope_theta": 1000000,
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": false,
|
||||
"torch_dtype": "bfloat16",
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||||
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|
||||
}
|
||||
}
|
||||
31
special_tokens_map.json
Normal file
31
special_tokens_map.json
Normal file
@@ -0,0 +1,31 @@
|
||||
{
|
||||
"additional_special_tokens": [
|
||||
"<|im_start|>",
|
||||
"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
||||
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|
||||
"<|box_start|>",
|
||||
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|
||||
"<|quad_start|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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||||
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|
||||
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|
||||
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|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
239
tokenizer_config.json
Normal file
239
tokenizer_config.json
Normal file
@@ -0,0 +1,239 @@
|
||||
{
|
||||
"add_bos_token": false,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
},
|
||||
"151654": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"151656": {
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"eos_token": "<|im_end|>",
|
||||
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|
||||
"extra_special_tokens": {},
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user