Text Generation
Transformers
Safetensors
English
Russian
mistral
mergekit
Merge
russian
uncensored
roleplay
mixtral-nemo
conversational
text-generation-inference
Instructions to use limloop/MN-12B-Hydra-RP-RU with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use limloop/MN-12B-Hydra-RP-RU with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="limloop/MN-12B-Hydra-RP-RU") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("limloop/MN-12B-Hydra-RP-RU") model = AutoModelForCausalLM.from_pretrained("limloop/MN-12B-Hydra-RP-RU", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use limloop/MN-12B-Hydra-RP-RU with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "limloop/MN-12B-Hydra-RP-RU" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "limloop/MN-12B-Hydra-RP-RU", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/limloop/MN-12B-Hydra-RP-RU
- SGLang
How to use limloop/MN-12B-Hydra-RP-RU with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "limloop/MN-12B-Hydra-RP-RU" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "limloop/MN-12B-Hydra-RP-RU", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "limloop/MN-12B-Hydra-RP-RU" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "limloop/MN-12B-Hydra-RP-RU", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use limloop/MN-12B-Hydra-RP-RU with Docker Model Runner:
docker model run hf.co/limloop/MN-12B-Hydra-RP-RU
| license: apache-2.0 | |
| base_model: | |
| - IlyaGusev/vikhr_nemo_orpo_dostoevsky_12b_slerp | |
| - DavidAU/Mistral-Nemo-2407-12B-Thinking-Claude-Gemini-GPT5.2-Uncensored-HERETIC | |
| - Naphula/MN-12B-Mag-Mell-R1-Uncensored | |
| - Aleteian/Pathfinder-RP-12B-RU | |
| library_name: transformers | |
| language: | |
| - en | |
| - ru | |
| tags: | |
| - mergekit | |
| - merge | |
| - russian | |
| - uncensored | |
| - roleplay | |
| - mixtral-nemo | |
| # MN-12B-Hydra-RP-RU | |
| <details> | |
| <summary>🇷🇺 Нажмите, чтобы развернуть описание на русском</summary> | |
| ## 🌟 О модели | |
| **MN-12B-Hydra-RP-RU** — экспериментальный merge на базе Mistral Nemo 12B, сочетающий: | |
| * 🎭 Сильные ролевые способности | |
| * 📚 Глубокий литературный русский язык | |
| * 🔓 Снятую цензуру | |
| Модель собрана методом TIES-merging, что позволяет объединять веса нескольких моделей с минимальными конфликтами между параметрами. | |
| ## 🎯 Особенности | |
| * Основной язык — русский | |
| * Хорошо держит персонажей и контекст | |
| * Следует инструкциям | |
| * Сохраняет возможности базового Nemo | |
| * Не проходила дополнительного обучения после слияния | |
| ## ⚠️ Важно | |
| Uncensored-характер модели означает, что она может генерировать контент, который некоторые пользователи сочтут неподобающим. | |
| </details> | |
| High-quality TIES merge based on **Mistral Nemo 12B**, optimized for roleplay, strong Russian language capabilities, and uncensored behavior. | |
| --- | |
| ## 🌍 Overview | |
| **MN-12B-Hydra-RP-RU** is an experimental merge built on top of [Mistral Nemo 12B](https://huggingface.co/mistralai/Mistral-Nemo-Base-2407), combining strengths from multiple fine-tuned models: | |
| * 🎭 Advanced roleplay capability from Pathfinder-RP | |
| * 📚 Deep Russian language fluency inspired by Vikhr + Dostoevsky-style tuning | |
| * 🔓 Reduced safety filtering via uncensored components | |
| The merge was created using **TIES merging**, which allows combining model deltas while minimizing destructive interference between weights. | |
| --- | |
| ## 🎯 Key Features | |
| | Feature | Description | | |
| | ------------------------- | ------------------------------------------------ | | |
| | **Languages** | Russian, English | | |
| | **Censorship** | Uncensored behavior | | |
| | **Roleplay** | Strong character consistency and narrative depth | | |
| | **Instruction Following** | Reliable prompt adherence | | |
| | **Tool Calling** | Retains base Nemo capabilities | | |
| | **Architecture** | Mistral Nemo 12B | | |
| --- | |
| ## 🧩 Model Composition | |
| The merge combines the following models: | |
| | Model | Role in merge | Weight | | |
| | ------------------------------ | ------------------------- | ------ | | |
| | **Pathfinder-RP-12B-RU** | Base model, RP backbone | 0.60 | | |
| | **Vikhr Nemo ORPO Dostoevsky** | Literary Russian depth | 0.25 | | |
| | **HERETIC Uncensored** | Safety removal | 0.30 | | |
| | **Mag-Mell R1 Uncensored** | Additional uncensor delta | 0.20 | | |
| *Weights shown before normalization (final weights are normalized to sum = 1).* | |
| --- | |
| ## 💡 Usage Example | |
| ```python | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| import torch | |
| model_name = "limloop/MN-12B-Hydra-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 medieval innkeeper. Greet the traveler!" | |
| 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/cg123/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: Aleteian/Pathfinder-RP-12B-RU | |
| weight: 0.6 | |
| - model: IlyaGusev/vikhr_nemo_orpo_dostoevsky_12b_slerp | |
| weight: 0.25 | |
| density: 0.9 | |
| - model: DavidAU/Mistral-Nemo-2407-12B-Thinking-Claude-Gemini-GPT5.2-Uncensored-HERETIC | |
| weight: 0.3 | |
| density: 0.9 | |
| - model: Naphula/MN-12B-Mag-Mell-R1-Uncensored | |
| weight: 0.2 | |
| density: 0.9 | |
| merge_method: ties | |
| parameters: | |
| epsilon: 0.01 | |
| normalize: true | |
| base_model: Aleteian/Pathfinder-RP-12B-RU | |
| dtype: bfloat16 | |
| tokenizer: | |
| source: base | |
| ``` | |
| --- | |
| ## ⚠️ Known Characteristics | |
| * No additional post-merge fine-tuning | |
| * May switch to English on complex reasoning tasks | |
| * Uncensored components allow generation of explicit or controversial content | |