---
tags:
- merge
- mergekit
- lazymergekit
- mlabonne/OmniBeagle-7B
- flemmingmiguel/MBX-7B-v3
- AiMavenAi/AiMaven-Prometheus
base_model:
- mlabonne/OmniBeagle-7B
- flemmingmiguel/MBX-7B-v3
- AiMavenAi/AiMaven-Prometheus
license: apache-2.0
---


# NeuralTrix-7B-v1

NeuralTrix-7B-v1 is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [mlabonne/OmniBeagle-7B](https://huggingface.co./mlabonne/OmniBeagle-7B)
* [flemmingmiguel/MBX-7B-v3](https://huggingface.co./flemmingmiguel/MBX-7B-v3)
* [AiMavenAi/AiMaven-Prometheus](https://huggingface.co./AiMavenAi/AiMaven-Prometheus)

It was then trained with DPO using: 
* https://huggingface.co./datasets/jondurbin/truthy-dpo-v0.1

## 🧩 Configuration

```yaml
models:
  - model: mistralai/Mistral-7B-v0.1
    # no parameters necessary for base model
  - model: mlabonne/OmniBeagle-7B
    parameters:
      density: 0.65
      weight: 0.4
  - model: flemmingmiguel/MBX-7B-v3
    parameters:
      density: 0.6
      weight: 0.35
  - model: AiMavenAi/AiMaven-Prometheus
    parameters:
      density: 0.6
      weight: 0.35
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: float16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "CultriX/NeuralTrix-7B-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"])
```