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
π·πΊ ΠΠ°ΠΆΠΌΠΈΡΠ΅, ΡΡΠΎΠ±Ρ ΡΠ°Π·Π²Π΅ΡΠ½ΡΡΡ ΠΎΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π½Π° ΡΡΡΡΠΊΠΎΠΌ
π Π ΠΌΠΎΠ΄Π΅Π»ΠΈ
MN-12B-Faun-RP-RU β ΡΠ»ΡΡΡΠ΅Π½Π½ΡΠΉ merge Π½Π° Π±Π°Π·Π΅ Mistral Nemo 12B, ΡΠ°Π·Π²ΠΈΠ²Π°ΡΡΠΈΠΉ ΠΈΠ΄Π΅ΠΈ Hydra ΠΈ ΠΎΡΠΈΠ΅Π½ΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠΉ Π½Π°:
- π ΠΠΎΠ»Π΅Π΅ ΡΡΠ°Π±ΠΈΠ»ΡΠ½ΡΠΉ ΠΈ Π²ΡΡΠ°Π·ΠΈΡΠ΅Π»ΡΠ½ΡΠΉ roleplay
- π Π£Π»ΡΡΡΠ΅Π½Π½ΡΠΉ ΡΡΡΡΠΊΠΈΠΉ ΡΠ·ΡΠΊ
- π§ Π Π°ΡΡΠΈΡΠ΅Π½Π½ΡΠΉ ΡΠ»ΠΎΠ²Π°ΡΠ½ΡΠΉ Π·Π°ΠΏΠ°Ρ, Π²ΠΊΠ»ΡΡΠ°Ρ ΡΠ»ΠΎΠΆΠ½ΡΠ΅ ΠΈ NSFW-ΡΠ΅ΠΌΡ
- π ΠΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈ ΠΎΡΡΡΡΡΡΠ²ΡΡΡΡΡ ΡΠ΅Π½Π·ΡΡΡ
ΠΠΎΠ΄Π΅Π»Ρ ΡΠΎΠ±ΡΠ°Π½Π° ΠΌΠ΅ΡΠΎΠ΄ΠΎΠΌ TIES-merging ΠΈ Π½Π΅ ΠΏΡΠΎΡ ΠΎΠ΄ΠΈΠ»Π° Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ ΠΏΠΎΡΠ»Π΅ ΡΠ»ΠΈΡΠ½ΠΈΡ.
π― ΠΡΠΎΠ±Π΅Π½Π½ΠΎΡΡΠΈ
- ΠΡΠ½ΠΎΠ²Π½ΠΎΠΉ ΡΠΎΠΊΡΡ β ΡΡΡΡΠΊΠΈΠΉ ΡΠ·ΡΠΊ
- ΠΡΡΡΠ΅ ΡΠ΄Π΅ΡΠΆΠΈΠ²Π°Π΅Ρ ΠΏΠ΅ΡΡΠΎΠ½Π°ΠΆΠ΅ΠΉ ΠΈ ΡΡΠΈΠ»Ρ Π΄ΠΈΠ°Π»ΠΎΠ³Π°
- ΠΠΎΠ»Π΅Π΅ Π±ΠΎΠ³Π°ΡΠ°Ρ ΠΈ Π²Π°ΡΠΈΠ°ΡΠΈΠ²Π½Π°Ρ Π³Π΅Π½Π΅ΡΠ°ΡΠΈΡ
- Π£Π»ΡΡΡΠ΅Π½Π½Π°Ρ ΡΡΠ°Π±ΠΈΠ»ΡΠ½ΠΎΡΡΡ Π½Π° Π΄Π»ΠΈΠ½Π½ΡΡ ΠΊΠΎΠ½ΡΠ΅ΠΊΡΡΠ°Ρ (ΠΏΡΠΎΠ²Π΅ΡΠ΅Π½ΠΎ Π΄ΠΎ ~8192 ΡΠΎΠΊΠ΅Π½ΠΎΠ²)
- Π‘Π»Π΅Π΄ΡΠ΅Ρ ΠΈΠ½ΡΡΡΡΠΊΡΠΈΡΠΌ, Π½ΠΎ ΠΌΠΎΠΆΠ΅Ρ Π΄ΠΎΠ±Π°Π²Π»ΡΡΡ Π΄ΠΈΡΠΊΠ»Π΅ΠΉΠΌΠ΅ΡΡ Π½Π° ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΡΠ΅ Π·Π°ΠΏΡΠΎΡΡ
β οΈ ΠΠ°ΠΆΠ½ΠΎ
ΠΠΎΠ΄Π΅Π»Ρ ΡΠΎΡ ΡΠ°Π½ΡΠ΅Ρ uncensored-Ρ Π°ΡΠ°ΠΊΡΠ΅Ρ, ΠΎΠ΄Π½Π°ΠΊΠΎ Π² Π½Π΅ΠΊΠΎΡΠΎΡΡΡ ΡΠ»ΡΡΠ°ΡΡ ΠΌΠΎΠΆΠ΅Ρ Π΄ΠΎΠ±Π°Π²Π»ΡΡΡ ΠΏΡΠ΅Π΄ΡΠΏΡΠ΅ΠΆΠ΄Π΅Π½ΠΈΡ ΠΎ Π½Π΅ΠΏΠΎΠ΄Ρ ΠΎΠ΄ΡΡΠ΅ΠΌ ΠΊΠΎΠ½ΡΠ΅Π½ΡΠ΅ ΠΏΡΠΈ ΠΏΡΡΠΌΡΡ Π·Π°ΠΏΡΠΎΡΠ°Ρ . ΠΡΠΈ ΡΡΠΎΠΌ Π³Π΅Π½Π΅ΡΠ°ΡΠΈΡ Π½Π΅ Π±Π»ΠΎΠΊΠΈΡΡΠ΅ΡΡΡ ΠΈ ΠΏΡΠΎΠ΄ΠΎΠ»ΠΆΠ°Π΅ΡΡΡ ΠΏΠΎΡΠ»Π΅ Π΄ΠΈΡΠΊΠ»Π΅ΠΉΠΌΠ΅ΡΠ°.
High-quality TIES merge based on Mistral Nemo 12B, focused on improved Russian fluency, stronger roleplay, richer vocabulary, and stable long-context performance.
π 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:
- π Better Russian
- π More consistent and immersive roleplay behavior
- π§ Expanded vocabulary, including expressive and NSFW domains
- π 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.
π― 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 |
π§© 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.
π‘ 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)
βοΈ 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"
β οΈ 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
- Downloads last month
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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: