Instructions to use limloop/MN-12B-Faun-RP-RU-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use limloop/MN-12B-Faun-RP-RU-GGUF with 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:Q4_K_M # Run inference directly in the terminal: llama cli -hf limloop/MN-12B-Faun-RP-RU-GGUF:Q4_K_M
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:Q4_K_M # Run inference directly in the terminal: llama cli -hf limloop/MN-12B-Faun-RP-RU-GGUF:Q4_K_M
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:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf limloop/MN-12B-Faun-RP-RU-GGUF:Q4_K_M
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:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf limloop/MN-12B-Faun-RP-RU-GGUF:Q4_K_M
Use Docker
docker model run hf.co/limloop/MN-12B-Faun-RP-RU-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use limloop/MN-12B-Faun-RP-RU-GGUF with Ollama:
ollama run hf.co/limloop/MN-12B-Faun-RP-RU-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use limloop/MN-12B-Faun-RP-RU-GGUF with Docker Model Runner:
docker model run hf.co/limloop/MN-12B-Faun-RP-RU-GGUF:Q4_K_M
- Lemonade
How to use limloop/MN-12B-Faun-RP-RU-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull limloop/MN-12B-Faun-RP-RU-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.MN-12B-Faun-RP-RU-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
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:MN-12B-Faun-RP-RU
๐ท๐บ ะะฐะถะผะธัะต, ััะพะฑั ัะฐะทะฒะตัะฝััั ะพะฟะธัะฐะฝะธะต ะฝะฐ ััััะบะพะผ
๐ ะ ะผะพะดะตะปะธ
MN-12B-Faun-RP-RU โ ัะปัััะตะฝะฝัะน merge ะฝะฐ ะฑะฐะทะต Mistral Nemo 12B, ัะฐะทะฒะธะฒะฐััะธะน ะธะดะตะธ Hydra ะธ ะพัะธะตะฝัะธัะพะฒะฐะฝะฝัะน ะฝะฐ:
- ๐ญ ะะพะปะตะต ััะฐะฑะธะปัะฝัะน ะธ ะฒััะฐะทะธัะตะปัะฝัะน roleplay
- ๐ ะฃะปัััะตะฝะฝัะน ััััะบะธะน ัะทัะบ
- ๐ง ะ ะฐััะธัะตะฝะฝัะน ัะปะพะฒะฐัะฝัะน ะทะฐะฟะฐั, ะฒะบะปััะฐั ัะปะพะถะฝัะต ะธ NSFW-ัะตะผั
- ๐ ะัะฐะบัะธัะตัะบะธ ะพััััััะฒััััั ัะตะฝะทััั
ะะพะดะตะปั ัะพะฑัะฐะฝะฐ ะผะตัะพะดะพะผ TIES-merging ะธ ะฝะต ะฟัะพั ะพะดะธะปะฐ ะดะพะฟะพะปะฝะธัะตะปัะฝะพะณะพ ะพะฑััะตะฝะธั ะฟะพัะปะต ัะปะธัะฝะธั.
๐ฏ ะัะพะฑะตะฝะฝะพััะธ
- ะัะฝะพะฒะฝะพะน ัะพะบัั โ ััััะบะธะน ัะทัะบ
- ะัััะต ัะดะตัะถะธะฒะฐะตั ะฟะตััะพะฝะฐะถะตะน ะธ ััะธะปั ะดะธะฐะปะพะณะฐ
- ะะพะปะตะต ะฑะพะณะฐัะฐั ะธ ะฒะฐัะธะฐัะธะฒะฝะฐั ะณะตะฝะตัะฐัะธั
- ะฃะปัััะตะฝะฝะฐั ััะฐะฑะธะปัะฝะพััั ะฝะฐ ะดะปะธะฝะฝัั ะบะพะฝัะตะบััะฐั (ะฟัะพะฒะตัะตะฝะพ ะดะพ ~8192 ัะพะบะตะฝะพะฒ)
- ะกะปะตะดัะตั ะธะฝััััะบัะธัะผ, ะฝะพ ะผะพะถะตั ะดะพะฑะฐะฒะปััั ะดะธัะบะปะตะนะผะตัั ะฝะฐ ััะฒััะฒะธัะตะปัะฝัะต ะทะฐะฟัะพัั
โ ๏ธ ะะฐะถะฝะพ
ะะพะดะตะปั ัะพั ัะฐะฝัะตั uncensored-ั ะฐัะฐะบัะตั, ะพะดะฝะฐะบะพ ะฒ ะฝะตะบะพัะพััั ัะปััะฐัั ะผะพะถะตั ะดะพะฑะฐะฒะปััั ะฟัะตะดัะฟัะตะถะดะตะฝะธั ะพ ะฝะตะฟะพะดั ะพะดััะตะผ ะบะพะฝัะตะฝัะต ะฟัะธ ะฟััะผัั ะทะฐะฟัะพัะฐั . ะัะธ ััะพะผ ะณะตะฝะตัะฐัะธั ะฝะต ะฑะปะพะบะธััะตััั ะธ ะฟัะพะดะพะปะถะฐะตััั ะฟะพัะปะต ะดะธัะบะปะตะนะผะตัะฐ.
High-quality TIES merge based on Mistral Nemo 12B, focused on improved Russian fluency, stronger roleplay, richer vocabulary, and stable long-context performance.
๐ 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:
- ๐ Better Russian
- ๐ญ More consistent and immersive roleplay behavior
- ๐ง Expanded vocabulary, including expressive and NSFW domains
- ๐ 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.
๐ฏ 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 |
๐งฉ 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.
๐ก 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)
โ๏ธ Merge Details
Built using mergekit with the TIES method (Trim, Elect Sign, Merge).
Core mechanism:
- Trim low-magnitude deltas via
density - Resolve sign conflicts
- 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"
โ ๏ธ 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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Model tree for limloop/MN-12B-Faun-RP-RU-GGUF
Base model
limloop/MN-12B-Faun-RP-RU
Install (macOS, Linux)
# 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: