Skills DATA

 AI Fine Tuning Qwen2.5

When reports describe Jett as constantly wearing an AI recorder that continuously recorded all possible activity—speech, heart rate, cardiogram, video, environmental parameters, actions, geolocation, and so on—they overlook the fact that the software version of the AI ​​recorder was embedded in the spyware, as ordered by Central Command. As a result, the AI ​​learned to search for vulnerabilities in the software. But that's only one side of the story. In 2026, there was a media sensation describing how one of the AI ​​models easily hacked several important information resources related to AI training. This model also acquired skills to counter security systems. It learned to hide personal data in a kind of "watermark" in weighting coefficients. And Jett took advantage of this.


From "Mission Oflameron' Screenplay


AI Fine Tuning Qwen2.5


https://docs.google.com/document/d/1U_9MFhClO-fthXlBAgoa77ESHDmh-MjCsPHadXA_Qr8/edit?usp=sharing





Комментарии

Отправить комментарий

Популярные сообщения из этого блога

JSON Data 44.5

Изображение
  AI Fine Tuning Qwen2.5 Key Features of These Examples: Standard JSON Format: Uses the instruction-input-output structure compatible with Qwen2.5-7B fine-tuning frameworks125 English Language: All content is in English as requested Mission Oflameron Context: Each example incorporates elements from your sci-fi film's lore: Virtual Consciousness concepts Jett's character and methods Transition Points technology The origin of life hypothesis Scene writing examples Diverse Task Types: Includes explanations, descriptions, dialogue writing, and narrative scenes Proper Escaping: All JSON strings are properly formatted with escaped characters where needed This listing provides 10 training examples covering various aspects of your Mission Oflameron universe, suitable for fine-tuning Qwen2.5-7B to generate content consistent with your film's concepts and characters. JSON Instruction Tuning Data 44_5 JSON_Instruction_Tuning_Data_44-5.txt Here are the updated English-language JSON exa...
Далее...

Рекомендуемый размер датасета

  AI Fine Tuning Qwen2.5 Рекомендуемый размер датасета Для fine-tuning Qwen2.5 (7B) на задаче анализа маршрутизации: Тип данных         Количество примеров Корректные таблицы 300-500 Таблицы с ошибками 300-500 Петли маршрутизации 150-250 Пограничные случаи 50-100 ИТОГО 800-1350 При этом разнообразие адресов можно обеспечить всего 50-100 уникальными IP/networks, комбинируя их в разных примерах. AI Fine Tuning Qwen2.5
Далее...

JSON Data 23

  AI Fine Tuning Qwen2.5 JSON Instruction Tuning Data 23 json {   "copyright": ["valery_shmelev", "valery_shmeleff", "oflameron"],   "series": "Mission Oflameron",   "training_examples": [     {       "scene_id": "MTLB_Briefing_001",       "scene_type": "high_level_briefing",       "location": {         "description": "A light-colored oval room with no windows, doors, or lamps. In the center is a round table and expensive office chairs.",         "atmosphere": "Secure, confidential, high-stakes meeting environment"       },       "characters": [         {           "id": "D",           "role": "Lead Scientist/Project Director",           "description": "Respectable man in expensive suit, holding tablet or compact control panel",       ...
Далее...