---
base_model:
- flammenai/Mahou-1.3-mistral-nemo-12B
- nbeerbower/mistral-nemo-gutenberg-12B-v4
- Sao10K/MN-12B-Lyra-v1
- Gryphe/Pantheon-RP-1.5-12b-Nemo
library_name: transformers
tags:
- mergekit
- merge
---

![cute](https://huggingface.co/matchaaaaa/MN-Tiramisu-12B/resolve/main/tiramisu-cute.png)

# MN-Tiramisu-12B

This is a really yappity-yappy yapping model that's good for long-form RP. Tried to rein it in with Mahou and give it some more character understanding with Pantheon. Feedback is always welcome.

**Native Context Length: 16K/16384** *(can be extended using RoPE, YMMV)*

## Prompt Template: ChatML

```
<|im_start|>system
{system prompt}<|im_end|>
<|im_start|>user
{message}<|im_end|>
<|im_start|>assistant
{response}
```

## Recommended Settings:

Here are some settings ranges that tend to work for me. They aren't strict values, and there's a bit of leeway in them. Feel free to experiment a bit!

* Temperature:        **1.0** (maybe less, a little bit goes a long way with Nemo)
* Min-P:              **0.1** to **0.2**
* *(all other samplers disabled)*

## Merge Details

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

### Merge Method

This model was merged using the linear [DARE](https://arxiv.org/abs/2311.03099) merge method using flammenai/Mahou-1.3-mistral-nemo-12B as a base.

### Models Merged

The following models were included in the merge:
* nbeerbower/mistral-nemo-gutenberg-12B-v4
* Sao10K/MN-12B-Lyra-v1
* Gryphe/Pantheon-RP-1.5-12b-Nemo
* flammenai/Mahou-1.3-mistral-nemo-12B

### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model: flammenai/Mahou-1.3-mistral-nemo-12B
dtype: bfloat16
merge_method: dare_linear
slices:
- sources:
  - layer_range: [0, 40]
    model: Gryphe/Pantheon-RP-1.5-12b-Nemo
    parameters:
      weight: [0.45, 0.35, 0.35, 0.2, 0.2]
  - layer_range: [0, 40]
    model: Sao10K/MN-12B-Lyra-v1
    parameters:
      weight: [0.25, 0.3, 0.35, 0.3, 0.2]
  - layer_range: [0, 40]
    model: nbeerbower/mistral-nemo-gutenberg-12B-v4
    parameters:
      weight:
      - filter: mlp
        value: [0.1, 0.2, 0.1, 0.4, 0.5]
      - value: [0.1, 0.2, 0.1, 0.2, 0.2]
  - layer_range: [0, 40]
    model: flammenai/Mahou-1.3-mistral-nemo-12B
    parameters:
      weight:
      - filter: mlp
        value: [0.2, 0.15, 0.2, 0.1, 0.1]
      - value: [0.2, 0.15, 0.2, 0.3, 0.4]
tokenizer_source: union
```

## Benchmarks (or Benchmark because I tried only one)

I ran EQ bench from [EleutherAI's lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness) (thank you @FallenMerick).

```
| Tasks  |Version|Filter|n-shot|     Metric      |   | Value  |   |Stderr|
|--------|------:|------|-----:|-----------------|---|-------:|---|-----:|
|eq_bench|    2.1|none  |     0|eqbench          |↑  | 79.3617|±  | 1.637|
|        |       |none  |     0|percent_parseable|↑  |100.0000|±  | 0.000|
```

And as always, have a great day!