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---
tags:
- merge
- mergekit
- lazymergekit
- MaziyarPanahi/Calme-7B-Instruct-v0.9
- yam-peleg/Experiment26-7B
base_model:
- MaziyarPanahi/Calme-7B-Instruct-v0.9
- yam-peleg/Experiment26-7B
license: cc-by-nc-4.0
---
# Myriad-7B-Slerp
Myriad-7B-Slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [MaziyarPanahi/Calme-7B-Instruct-v0.9](https://huggingface.co/MaziyarPanahi/Calme-7B-Instruct-v0.9)
* [yam-peleg/Experiment26-7B](https://huggingface.co/yam-peleg/Experiment26-7B)
Special thanks to Charles Goddard for the quick implementation!
## 🧩 Configuration
```yaml
slices:
- sources:
- model: MaziyarPanahi/Calme-7B-Instruct-v0.9
layer_range: [0, 32]
- model: yam-peleg/Experiment26-7B
layer_range: [0, 32]
merge_method: slerp
base_model: yam-peleg/Experiment26-7B
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: float16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Muhammad2003/Myriad-7B-Slerp"
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"])
```
## 🏆 Evaluation
| Task | Score |
|---------------|---------|
| ARC | 73.38 |
| Hellaswag | 89.05 |
| MMLU | 64.32 |
| TruthfulQA | 77.95 |
| Winogrande | 84.85 |
| GSM8k | 70.28 |
|