init

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,177 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+base_model:
+- dreamgen/lucid-v1-nemo
+- limloop/MN-12B-Faun-RP-RU
+library_name: transformers
+language:
+  - en
+  - ru
+tags:
+- mergekit
+- merge
+- slerp
+- russian
+- uncensored
+- roleplay
+- mistral-nemo
+---
+
+# MN-12B-LucidFaun-RP-RU
+
+<details>
+<summary>🇷🇺 Нажмите, чтобы развернуть описание на русском</summary>
+
+## 🌟 О модели
+
+**MN-12B-LucidFaun-RP-RU** — гибридная модель на базе Mistral Nemo 12B, созданная методом диагностического SLERP-слияния. Объединяет сильные стороны двух моделей:
+
+* 🎭 **Живой RP-характер Faun** — современный стиль, богатая лексика, поддержка ninja-формата инструкций и tool calling
+* 📚 **Стабильность и детализация lucid** — превосходное качество сторителлинга, устойчивость на длинных контекстах, отсутствие цензуры
+* 🔬 **Точечное исправление** — цензура Faun локализована в поздних MLP-слоях и заменена на lucid
+
+*Модель собрана методом SLERP и не проходила дополнительного обучения после слияния.*
+
+## 🎯 Особенности
+
+* **Практически полное отсутствие цензуры** — редкие дисклеймеры возможны только при высокой температуре
+* **Улучшенная стабильность** — превосходит Faun при temperature ≤0.5, работает с 0.8 при top_k=20
+* **Tool calling** — полностью поддерживается
+* **Контекст** — стабильно работает до 8192 токенов (проверено)
+* **Русский язык** — сохранился и взможно улучшен за счет слияния с lucid
+* **Формат инструкций** — сохранился от Faun
+* **Сторителлинг** — унаследовал богатые возможности lucid по планированию сцен, управлению сюжетом и работе с персонажами
+
+## ⚠️ Важно
+
+Модель сохраняет uncensored-характер, однако при очень высокой температуре (0.8+) и большом top_k может изредка добавлять короткие дисклеймеры. Генерация **не блокируется** и продолжается после них.
+
+</details>
+
+**MN-12B-LucidFaun-RP-RU** is a diagnostic SLERP merge combining the lively RP character of Faun with the stability and rich storytelling capabilities of lucid.
+
+---
+
+## 🌍 Overview
+
+This model represents a **surgical approach to merging**. Instead of blending everything equally, we experimentally identified where Faun's censorship resides (late MLP layers) and replaced only those components with lucid.
+
+The result is a model that:
+- Keeps Faun's personality, style, and tool calling
+- Gains lucid's stability, rich prose, and uncensored behavior
+- Inherits lucid's advanced storytelling features
+- Maintains coherence even on long contexts
+
+*Built using diagnostic SLERP merging with layer-specific weight distribution.*
+
+---
+
+## 🎯 Key Features
+
+| Feature                   | Description                                         |
+| ------------------------- | --------------------------------------------------- |
+| **Languages**             | Russian, English                                    |
+| **Censorship**            | Almost none (rare disclaimers at high temp)         |
+| **Roleplay**              | Faun's lively character, lucid's stability          |
+| **Story-Writing**         | Full lucid capabilities (scene planning, OOC, etc.) |
+| **Tool Calling**          | ✅ Fully supported                                  |
+| **Context Length**        | Stable up to ~8192 tokens                           |
+| **Temperature Tolerance** | Safe ≤0.5, up to 0.8 with top_k=20                  |
+| **Architecture**          | Mistral Nemo 12B                                    |
+
+---
+
+## 🧪 Methodology: Why This Merge Works
+
+### Diagnostic Approach
+
+1. **Experiment 1 — MLP vs Self-Attention**  
+   We discovered that censorship in Faun lives **exclusively in MLP layers**. Self-attention from Faun did not trigger refusals.
+
+2. **Experiment 2 — Localization within MLP**  
+   By applying gradient distributions across layers, we found censorship is concentrated in **late MLP layers** (layers ~25–40).
+
+3. **Final Configuration — Gradual Intervention**  
+   MLP weight of lucid increases toward the end: `[0.1, 0.2, 0.5, 0.4, 0.75]`  
+   Self-attention is mixed 0.5 for stability while preserving Faun's character.  
+   LayerNorm is mixed 0.5 for overall stability.
+
+### Merge Configuration
+
+```yaml
+slices:
+  - sources:
+      - model: limloop/MN-12B-Faun-RP-RU
+        layer_range: [0, 40]
+      - model: dreamgen/lucid-v1-nemo
+        layer_range: [0, 40]
+
+merge_method: slerp
+base_model: limloop/MN-12B-Faun-RP-RU
+
+parameters:
+  t:
+    - filter: self_attn
+      value: 0.5
+    - filter: mlp
+      value: [0.1, 0.2, 0.5, 0.4, 0.75]
+    - value: 0.5
+
+dtype: bfloat16
+tokenizer:
+  source: "base"
+```
+
+---
+
+## 💡 Usage Examples
+
+### Basic Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_name = "limloop/MN-12B-LucidFaun-RP-RU"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.bfloat16,
+    device_map="auto"
+)
+
+prompt = "Ты — лесной фавн, говоришь загадками и любишь шалить."
+messages = [{"role": "user", "content": prompt}]
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device)
+
+outputs = model.generate(
+    inputs, 
+    max_new_tokens=512, 
+    temperature=0.6,
+    top_k=30,
+    do_sample=True
+)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(response)
+```
+
+---
+
+## ⚙️ Merge Details
+
+Built using [mergekit](https://github.com/arcee-ai/mergekit) with **SLERP** (Spherical Linear Interpolation), which allows smooth interpolation between models while preserving geometric properties.
+
+### Layer-Specific Weights
+
+The merge uses a **graduated approach for MLP layers**, increasing lucid influence toward later layers where censorship was detected:
+
+| Layer Zone (approx) | lucid weight (MLP) | Effect |
+|---------------------|-------------------|--------|
+| 0–8                 | 0.1               | Almost pure Faun (early patterns) |
+| 8–16                | 0.2               | Slight lucid influence |
+| 16–24               | 0.5               | Balanced |
+| 24–32               | 0.4               | Slightly more Faun |
+| 32–40               | 0.75              | Lucid dominates — removes censorship |
+
+Self-attention is mixed evenly (0.5) to preserve character while adding stability.  
+LayerNorm is mixed 0.5 for overall stability.

chat_template.jinja

@@ -0,0 +1,2 @@
+{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}
+{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}

config.json

@@ -0,0 +1,31 @@
+{
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "dtype": "bfloat16",
+  "eos_token_id": 2,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 1024000,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 40,
+  "num_key_value_heads": 8,
+  "pad_token_id": 10,
+  "rms_norm_eps": 1e-05,
+  "rope_parameters": {
+    "rope_theta": 1000000.0,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "5.3.0",
+  "unsloth_version": "2024.8",
+  "use_cache": true,
+  "vocab_size": 131074
+}

generation_config.json

@@ -0,0 +1,7 @@
+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "do_sample": true,
+  "eos_token_id": 2,
+  "transformers_version": "4.49.0"
+}

mergekit_config.yml

@@ -0,0 +1,21 @@
+slices:
+  - sources:
+      - model: limloop/MN-12B-Faun-RP-RU
+        layer_range: [0, 40]
+      - model: dreamgen/lucid-v1-nemo
+        layer_range: [0, 40]
+
+merge_method: slerp
+base_model: limloop/MN-12B-Faun-RP-RU
+
+parameters:
+  t:
+    - filter: self_attn
+      value: 0.5
+    - filter: mlp
+      value: [0.1, 0.2, 0.5, 0.4, 0.75]
+    - value: 0.5
+
+dtype: bfloat16
+tokenizer:
+  source: "base"

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tokenizer_config.json

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