---
tags:
- merge
- mergekit
base_model:
- SanjiWatsuki/Kunoichi-DPO-v2-7B
- CultriX/NeuralTrix-7B-dpo
---

# KuTrix-7b

This is a merge of pre-trained language models created using mergekit.

## Merge Details
### Merge Method

This model was merged using the **DARE TIES**  merge method using [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) as a base.


### Models Merged
The following models were included in the merge:
* [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co/SanjiWatsuki/Kunoichi-DPO-v2-7B)
* [CultriX/NeuralTrix-7B-dpo](https://huggingface.co/CultriX/NeuralTrix-7B-dpo)

##  Configuration
The following YAML configuration was used to produce this model:
```yaml
models:
  - model: mistralai/Mistral-7B-v0.1
    # No parameters necessary for base model
  - model: SanjiWatsuki/Kunoichi-DPO-v2-7B
    parameters:
      weight: 0.49
      density: 0.6
  - model: CultriX/NeuralTrix-7B-dpo
    parameters:
      weight: 0.4
      density: 0.6
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: bfloat16
```
## Usage Example

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "seyf1elislam/KuTrix-7b"
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"])
```