---
tags:
- merge
- mergekit
- lazymergekit
library_name: transformers
pipeline_tag: text-generation
---

# NemoDori-v0.1-12B-MS

NemoDori-v0.1-12B-MS is a MODEL STOCK merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing) (see below for merge configuration. All credits to them.)

This is my 'first' merge model, just for testing purpose. I don't know what I'm doing, honestly...

My experience using this in SillyTavern:
- It advances the story slowly, responding to the last message quite nicely.
- Creativity is good, sometimes surprising me with a similar response that I'd like to get.
- It may skip time when the last message includes word(s) that resemble a promise (or literally time).
- Sometimes it responds with a long response, but it's kind of adapted to the overall roleplay, i think...


## Prompt and Preset

**ChatML** works best so far. **Llama3** and **Mistral** prompts work, but sometimes they speak for you. (ChatML may also speak for you, but not that often - simply re-generate.)

I use context and instruct from **[here](https://huggingface.co/Virt-io/SillyTavern-Presets/tree/main/Prompts/ChatML/v1.9)** (Credits to **[Virt-io](https://huggingface.co/Virt-io)**.)

**[This](https://pastebin.com/4jSq8V4N)** is the preset I use for SillyTavern, it should be good enough.
Tweak to your heart's content:
- **temp** can go higher (i stopped at 2),
- **skip special tokens** may or may not be needed. If it responds with "assistant" or "user" at the end, try **disabling** the checkbox. (i did get it in my first couple of tries, but now, no more. not sure why...)
- **context length** so far still coherence at **28k tokens**, based on my own testing.
- everything else is... just fine, as long as you're not forcing it.


## 🧩 Configuration

```yaml
models:
  - model: Sao10K/MN-12B-Lyra-v1
  - model: Fizzarolli/MN-12b-Rosier-v1
  - model: MarinaraSpaghetti/Nemomix-v4.0-12B
  - model: aetherwiing/MN-12B-Starcannon-v2
merge_method: model_stock
base_model: aetherwiing/MN-12B-Starcannon-v2
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "RozGrov/NemoDori-v0.1-12B-MS"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```