README.md

---
tags:
- merge
- mergekit
- lazymergekit
- liminerity/M7-7b
- Kukedlc/Neural4gsm8k
- Kukedlc/Jupiter-k-7B-slerp
- Kukedlc/NeuralMaxime-7B-slerp
- Kukedlc/NeuralFusion-7b-Dare-Ties
- Kukedlc/Neural-Krishna-Multiverse-7b-v3
- Kukedlc/NeuTrixOmniBe-DPO
- Kukedlc/NeuralSirKrishna-7b
base_model:
- liminerity/M7-7b
- Kukedlc/Neural4gsm8k
- Kukedlc/Jupiter-k-7B-slerp
- Kukedlc/NeuralMaxime-7B-slerp
- Kukedlc/NeuralFusion-7b-Dare-Ties
- Kukedlc/Neural-Krishna-Multiverse-7b-v3
- Kukedlc/NeuTrixOmniBe-DPO
- Kukedlc/NeuralSirKrishna-7b
license: apache-2.0
---

# MyModelsMerge-7b

MyModelsMerge-7b is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [liminerity/M7-7b](https://huggingface.co/liminerity/M7-7b)
* [Kukedlc/Neural4gsm8k](https://huggingface.co/Kukedlc/Neural4gsm8k)
* [Kukedlc/Jupiter-k-7B-slerp](https://huggingface.co/Kukedlc/Jupiter-k-7B-slerp)
* [Kukedlc/NeuralMaxime-7B-slerp](https://huggingface.co/Kukedlc/NeuralMaxime-7B-slerp)
* [Kukedlc/NeuralFusion-7b-Dare-Ties](https://huggingface.co/Kukedlc/NeuralFusion-7b-Dare-Ties)
* [Kukedlc/Neural-Krishna-Multiverse-7b-v3](https://huggingface.co/Kukedlc/Neural-Krishna-Multiverse-7b-v3)
* [Kukedlc/NeuTrixOmniBe-DPO](https://huggingface.co/Kukedlc/NeuTrixOmniBe-DPO)
* [Kukedlc/NeuralSirKrishna-7b](https://huggingface.co/Kukedlc/NeuralSirKrishna-7b)

## 🧩 Configuration
 
```yaml
models:
  - model: Kukedlc/NeuralSirKrishna-7b
    # no parameters necessary for base model
  - model: liminerity/M7-7b
    parameters:
      weight: 0.1
      density: 0.88
  - model: Kukedlc/Neural4gsm8k
    parameters:
      weight: 0.1
      density: 0.66
  - model: Kukedlc/Jupiter-k-7B-slerp
    parameters:
      weight: 0.1
      density: 0.66
  - model: Kukedlc/NeuralMaxime-7B-slerp
    parameters:
      weight: 0.1
      density: 0.44
  - model: Kukedlc/NeuralFusion-7b-Dare-Ties
    parameters:
      weight: 0.1
      density: 0.44
  - model: Kukedlc/Neural-Krishna-Multiverse-7b-v3
    parameters:
      weight: 0.2
      density: 0.66
  - model: Kukedlc/NeuTrixOmniBe-DPO
    parameters:
      weight: 0.1
      density: 0.33
  - model: Kukedlc/NeuralSirKrishna-7b
    parameters:
      weight: 0.2
      density: 0.88
merge_method: dare_ties
base_model: Kukedlc/NeuralSirKrishna-7b

parameters:
  int8_mask: true
  normalize: true
dtype: bfloat16
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Kukedlc/MyModelsMerge-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"])
```