Update active LoRA adapter (step 400/4320)

README.md

@@ -1,80 +1,210 @@
 ---
-language:
-- ru
-- en
-license: apache-2.0
+base_model: unsloth/Ministral-3-3B-Instruct-2512-bnb-4bit
+library_name: peft
 pipeline_tag: text-generation
 tags:
-- reasoning
-- deepseek-r1
-- ru-deepthink-mega
-- mistral
-- ministral
-- text-generation
-- gguf
-- godot
-- procedural-generation
+- base_model:adapter:unsloth/Ministral-3-3B-Instruct-2512-bnb-4bit
+- lora
+- sft
+- transformers
+- trl
+- unsloth
 ---
 
-# 🧠 Fwizzer-R1-3B-RU-v2
+# Model Card for Model ID
 
-<div align="center">
+<!-- Provide a quick summary of what the model is/does. -->
 
-**Вторая улучшенная версия мыслящей языковой модели Fwizzer-R1**
-*The Second Generation of Fwizzer-R1 Reasoning LLM*
 
-[![Dataset](https://img.shields.io/badge/Dataset-ru--deepthink--mega-blue)](https://huggingface.co/datasets/fwizzer1/ru-deepthink-mega)
-[![License](https://img.shields.io/badge/License-Apache%202.0-green)](LICENSE)
 
-</div>
+## Model Details
 
----
+### Model Description
 
-## 🇷🇺 Описание на русском
+<!-- Provide a longer summary of what this model is. -->
 
-**Fwizzer-R1-3B-RU-v2** — это компактная, но глубоко мыслящая языковая модель, дообученная на флагманском мега-датасете [**`fwizzer1/ru-deepthink-mega`**](https://huggingface.co/datasets/fwizzer1/ru-deepthink-mega) (17 281 пример со 100% размышлениями).
 
-### 🚀 Ключевые преимущества версии v2:
-1. **100% Reasoning:** Модель ВСЕГДА сначала размышляет внутри блока `<think> ... </think>` перед формированием ответа.
-2. **Думание в стоке (Stock Thinking):** В GGUF зашит шаблон `chat_template.jinja`, открывающий тег `<think>` автоматически даже без системного промпта.
-3. **Процедурная генерация & Godot 4 GDScript:** Глубокие знания игровых алгоритмов (клеточные автоматы для пещер, BSP комнаты/подземелья, шум Перлина, лабиринты, генерация лута и аффиксов).
-4. **Защита от логических капканов:** Уверенно решает ловушки токенизации (9.11 vs 9.9, подсчёт букв в словах, парадокс Монти Холла, управление ресурсами).
-5. **Самопроверка (Self-Correction):** Умеет перепроверять свои шаги, пересчитывать формулы и исправлять собственные ошибки на лету.
 
----
+- **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]
 
-## 🇬🇧 English Description
+### Model Sources [optional]
 
-**Fwizzer-R1-3B-RU-v2** is an advanced, lightweight reasoning language model fine-tuned on the comprehensive [**`fwizzer1/ru-deepthink-mega`**](https://huggingface.co/datasets/fwizzer1/ru-deepthink-mega) dataset (17 281 verified Chain-of-Thought samples).
+<!-- Provide the basic links for the model. -->
 
-### 🚀 Key Improvements in v2:
-1. **100% Reasoning by Default:** The model methodically analyzes problems inside `<think> ... </think>` tags before delivering the final answer.
-2. **Built-in Stock Thinking:** Native `chat_template.jinja` automatically activates `<think>` tags without requiring custom system prompts.
-3. **Procedural Generation & Game Development:** Specialized knowledge in **Godot 4 GDScript** and **Python** (Cellular Automata caves, BSP dungeon generators, Perlin noise biomes, A* pathfinding, dynamic item affix generation).
-4. **Tokenizer & Logic Trap Immunity:** Handles subtle math/logic pitfalls (e.g. 9.11 vs 9.9, letter counting in words, Monty Hall problem).
-5. **Self-Correction & Reflection:** Capable of reconsidering intermediate reasoning steps and verifying mathematical correctness on the fly.
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
 
----
+## Uses
 
-## 📦 Доступные квантизации GGUF / Available GGUF Models:
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
-| Файл | Квантование | Размер | Описание / Description |
-| :--- | :---: | :---: | :--- |
-| **`Fwizzer-R1-3B-v2Speed.gguf`** | Q4_K_M | ~2.0 GB | Лёгкая и быстрая, запуск на любых ПК и смартфонах / Ultra-fast inference |
-| **`Fwizzer-R1-3B-v2Balanced.gguf`** | Q5_K_M | ~2.4 GB | Золотая середина между скоростью и интеллектом / Recommended balance |
-| **`Fwizzer-R1-3B-v2Max.gguf`** | Q8_0 | ~3.4 GB | Максимальный интеллект, точность без потерь / Maximum reasoning quality |
+### Direct Use
 
----
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+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
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+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]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
 
-## 🛠️ Запуск в LM Studio / Ollama:
+## Model Card Contact
 
-1. Скачайте нужную квантизацию GGUF (например, `Fwizzer-R1-3B-v2Balanced.gguf`).
-2. Пресет `Fwizzer-R1.preset.json` уже находится в репозитории — LM Studio автоматически свернёт рассуждения в красивый блок **Thought**.
-3. **Шаблон вывода:**
-```
-<think>
-[Пошаговый ход мысли модели...]
-</think>
+[More Information Needed]
+### Framework versions
 
-[Финальный структурированный ответ]
-```
+- PEFT 0.19.1

adapter_model.safetensors

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