---
license: apache-2.0
base_model:
- ReadyArt/Forgotten-Safeword-12B-v4.0
- limloop/MN-12B-Hydra-RP-RU
- SicariusSicariiStuff/Impish_Bloodmoon_12B
library_name: transformers
language:
  - en
  - ru
tags:
- mergekit
- merge
- russian
- uncensored
- roleplay
- mixtral-nemo
---

# MN-12B-Faun-RP-RU

<details>
<summary>🇷🇺 Нажмите, чтобы развернуть описание на русском</summary>

## 🌟 О модели

**MN-12B-Faun-RP-RU** — улучшенный merge на базе Mistral Nemo 12B, развивающий идеи Hydra и ориентированный на:

* 🎭 Более стабильный и выразительный roleplay
* 📚 Улучшенный русский язык
* 🧠 Расширенный словарный запас, включая сложные и NSFW-темы
* 🔓 Практически отсутствующую цензуру

*Модель собрана методом TIES-merging и не проходила дополнительного обучения после слияния.*

## 🎯 Особенности

* Основной фокус — русский язык
* Лучше удерживает персонажей и стиль диалога
* Более богатая и вариативная генерация
* Улучшенная стабильность на длинных контекстах (проверено до ~8192 токенов)
* Следует инструкциям, но может добавлять дисклеймеры на чувствительные запросы

## ⚠️ Важно

Модель сохраняет uncensored-характер, однако в некоторых случаях может добавлять предупреждения о неподходящем контенте при прямых запросах.
При этом генерация **не блокируется** и продолжается после дисклеймера.

</details>

High-quality TIES merge based on **Mistral Nemo 12B**, focused on improved Russian fluency, stronger roleplay, richer vocabulary, and stable long-context performance.

---

## 🌍 Overview

**MN-12B-Faun-RP-RU** is an evolution of the Hydra-style merge, designed to push further in roleplay quality, language richness, and generation stability.

Key improvements include:

* 📚 Better Russian
* 🎭 More consistent and immersive roleplay behavior
* 🧠 Expanded vocabulary, including expressive and NSFW domains
* 🔁 More stable handling of long conversations (tested up to ~8k tokens)

The model may occasionally produce **safety disclaimers** when prompted directly for sensitive content, but generation continues normally afterward.

*Built using TIES merging, which minimizes destructive interference between merged model weights.*

---

## 🎯 Key Features

| Feature                   | Description                                     |
| ------------------------- | ----------------------------------------------- |
| **Languages**             | Russian, English                                |
| **Censorship**            | Mostly uncensored (with occasional disclaimers) |
| **Roleplay**              | Improved consistency and immersion              |
| **Instruction Following** | Strong                                          |
| **Vocabulary**            | Expanded, including NSFW domains                |
| **Context Length**        | Stable up to ~8192 tokens                       |
| **Architecture**          | Mistral Nemo 12B                                |

---

## 🧩 Model Composition

The merge combines the following models:

| Model                           | Role in merge       | Weight |
| ------------------------------- | ------------------- | ------ |
| **MN-12B-Hydra-RP-RU**          | Base / foundation   | 0.60   |
| **Impish_Bloodmoon_12B**        | RP + style boost    | 0.25   |
| **Forgotten-Safeword-12B-v4.0** | Uncensored behavior | 0.10   |

*Weights shown before normalization.*

---

## 💡 Usage Example

```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_name = "limloop/MN-12B-Faun-RP-RU"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
    model_name,
    torch_dtype=torch.bfloat16,
    device_map="auto"
)

prompt = "You are a mysterious forest faun speaking in poetic Russian."
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=0.7)
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
print(response)
```

---

## ⚙️ Merge Details

Built using [mergekit](https://github.com/arcee-ai/mergekit) with the **TIES** method (Trim, Elect Sign, Merge).

Core mechanism:

1. Trim low-magnitude deltas via `density`
2. Resolve sign conflicts
3. Weighted averaging of aligned parameters

### Merge Configuration

```yaml
models:
  - model: limloop/MN-12B-Hydra-RP-RU
    parameters:
      weight: 0.6

  - model: SicariusSicariiStuff/Impish_Bloodmoon_12B
    parameters:
      weight: 0.25
      density: 0.9

  - model: ReadyArt/Forgotten-Safeword-12B-v4.0
    parameters:
      weight: 0.1
      density: 0.6

merge_method: ties
parameters:
  epsilon: 0.01
  normalize: true

base_model: limloop/MN-12B-Hydra-RP-RU
dtype: bfloat16

tokenizer:
  source: "base"
```

---

## ⚠️ Known Characteristics

* No post-merge fine-tuning
* May produce safety disclaimers before sensitive outputs
* Occasionally switches to English in complex reasoning
* Stronger stylistic bias in roleplay compared to Hydra