How to use from
llama.cpp
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf limloop/MN-12B-Faun-RP-RU-GGUF:
# Run inference directly in the terminal:
llama cli -hf limloop/MN-12B-Faun-RP-RU-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf limloop/MN-12B-Faun-RP-RU-GGUF:
# Run inference directly in the terminal:
llama cli -hf limloop/MN-12B-Faun-RP-RU-GGUF:
Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf limloop/MN-12B-Faun-RP-RU-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf limloop/MN-12B-Faun-RP-RU-GGUF:
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf limloop/MN-12B-Faun-RP-RU-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf limloop/MN-12B-Faun-RP-RU-GGUF:
Use Docker
docker model run hf.co/limloop/MN-12B-Faun-RP-RU-GGUF:
Quick Links

MN-12B-Faun-RP-RU

Original model

πŸ‡·πŸ‡Ί НаТмитС, Ρ‡Ρ‚ΠΎΠ±Ρ‹ Ρ€Π°Π·Π²Π΅Ρ€Π½ΡƒΡ‚ΡŒ описаниС Π½Π° русском

🌟 О модСли

MN-12B-Faun-RP-RU β€” ΡƒΠ»ΡƒΡ‡ΡˆΠ΅Π½Π½Ρ‹ΠΉ merge Π½Π° Π±Π°Π·Π΅ Mistral Nemo 12B, Ρ€Π°Π·Π²ΠΈΠ²Π°ΡŽΡ‰ΠΈΠΉ ΠΈΠ΄Π΅ΠΈ Hydra ΠΈ ΠΎΡ€ΠΈΠ΅Π½Ρ‚ΠΈΡ€ΠΎΠ²Π°Π½Π½Ρ‹ΠΉ Π½Π°:

  • 🎭 Π‘ΠΎΠ»Π΅Π΅ ΡΡ‚Π°Π±ΠΈΠ»ΡŒΠ½Ρ‹ΠΉ ΠΈ Π²Ρ‹Ρ€Π°Π·ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹ΠΉ roleplay
  • πŸ“š Π£Π»ΡƒΡ‡ΡˆΠ΅Π½Π½Ρ‹ΠΉ русский язык
  • 🧠 Π Π°ΡΡˆΠΈΡ€Π΅Π½Π½Ρ‹ΠΉ словарный запас, Π²ΠΊΠ»ΡŽΡ‡Π°Ρ слоТныС ΠΈ NSFW-Ρ‚Π΅ΠΌΡ‹
  • πŸ”“ ΠŸΡ€Π°ΠΊΡ‚ΠΈΡ‡Π΅ΡΠΊΠΈ ΠΎΡ‚ΡΡƒΡ‚ΡΡ‚Π²ΡƒΡŽΡ‰ΡƒΡŽ Ρ†Π΅Π½Π·ΡƒΡ€Ρƒ

МодСль собрана ΠΌΠ΅Ρ‚ΠΎΠ΄ΠΎΠΌ TIES-merging ΠΈ Π½Π΅ ΠΏΡ€ΠΎΡ…ΠΎΠ΄ΠΈΠ»Π° Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎΠ³ΠΎ обучСния послС слияния.

🎯 ΠžΡΠΎΠ±Π΅Π½Π½ΠΎΡΡ‚ΠΈ

  • Основной фокус β€” русский язык
  • Π›ΡƒΡ‡ΡˆΠ΅ ΡƒΠ΄Π΅Ρ€ΠΆΠΈΠ²Π°Π΅Ρ‚ пСрсонаТСй ΠΈ ΡΡ‚ΠΈΠ»ΡŒ Π΄ΠΈΠ°Π»ΠΎΠ³Π°
  • Π‘ΠΎΠ»Π΅Π΅ богатая ΠΈ вариативная гСнСрация
  • Π£Π»ΡƒΡ‡ΡˆΠ΅Π½Π½Π°Ρ ΡΡ‚Π°Π±ΠΈΠ»ΡŒΠ½ΠΎΡΡ‚ΡŒ Π½Π° Π΄Π»ΠΈΠ½Π½Ρ‹Ρ… контСкстах (ΠΏΡ€ΠΎΠ²Π΅Ρ€Π΅Π½ΠΎ Π΄ΠΎ ~8192 Ρ‚ΠΎΠΊΠ΅Π½ΠΎΠ²)
  • Π‘Π»Π΅Π΄ΡƒΠ΅Ρ‚ инструкциям, Π½ΠΎ ΠΌΠΎΠΆΠ΅Ρ‚ Π΄ΠΎΠ±Π°Π²Π»ΡΡ‚ΡŒ дисклСймСры Π½Π° Ρ‡ΡƒΠ²ΡΡ‚Π²ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Π΅ запросы

⚠️ Π’Π°ΠΆΠ½ΠΎ

МодСль сохраняСт uncensored-Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€, ΠΎΠ΄Π½Π°ΠΊΠΎ Π² Π½Π΅ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Ρ… случаях ΠΌΠΎΠΆΠ΅Ρ‚ Π΄ΠΎΠ±Π°Π²Π»ΡΡ‚ΡŒ прСдупрСТдСния ΠΎ нСподходящСм ΠΊΠΎΠ½Ρ‚Π΅Π½Ρ‚Π΅ ΠΏΡ€ΠΈ прямых запросах. ΠŸΡ€ΠΈ этом гСнСрация Π½Π΅ блокируСтся ΠΈ продолТаСтся послС дисклСймСра.

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:

  • πŸ“š Better Russian
  • 🎭 More consistent and immersive roleplay behavior
  • 🧠 Expanded vocabulary, including expressive and NSFW domains
  • πŸ” 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.


πŸ’‘ Usage Example

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)

βš™οΈ Merge Details

Built using 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

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
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