---
base_model:
- UsernameJustAnother/Nemo-12B-Marlin-v5
- Sao10K/MN-12B-Lyra-v1
tags:
- merge
- mergekit
- lazymergekit
- UsernameJustAnother/Nemo-12B-Marlin-v5
- Sao10K/MN-12B-Lyra-v1
---

# Lyralin-12B-v1

Lyralin-12B-v1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [UsernameJustAnother/Nemo-12B-Marlin-v5](https://huggingface.co/UsernameJustAnother/Nemo-12B-Marlin-v5)
* [Sao10K/MN-12B-Lyra-v1](https://huggingface.co/Sao10K/MN-12B-Lyra-v1)

## 🧩 Configuration

```yaml
models:
  - model: UsernameJustAnother/Nemo-12B-Marlin-v5
    parameters:
      density: 0.4
      weight: 0.70
  - model: Sao10K/MN-12B-Lyra-v1
    parameters:
      density: 0.6
      weight: 0.30

merge_method: ties
base_model: UsernameJustAnother/Nemo-12B-Marlin-v5
parameters:
  normalize: true
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "GalrionSoftworks/Lyralin-12B-v1"
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"])
```