---
tags:
- merge
- mergekit
- lazymergekit
- jsfs11/MoEv4Config-TestWeightedTIES-7b
- nlpguy/AlloyIngot
base_model:
- jsfs11/MoEv4Config-TestWeightedTIES-7b
- nlpguy/AlloyIngot
---

# RandomMergeWEIGHTED-7B-SLERP

RandomMergeWEIGHTED-7B-SLERP is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [jsfs11/MoEv4Config-TestWeightedTIES-7b](https://huggingface.co/jsfs11/MoEv4Config-TestWeightedTIES-7b)
* [nlpguy/AlloyIngot](https://huggingface.co/nlpguy/AlloyIngot)

## 🧩 Configuration

```yaml
base_model: nlpguy/AlloyIngot
dtype: bfloat16
merge_method: slerp
parameters:
  t:
  - filter: self_attn
    value: [0.0, 0.3, 0.5, 0.7, 1.0]
  - filter: mlp
    value: [1.0, 0.7, 0.5, 0.3, 0.0]
  - value: 0.5
slices:
- sources:
  - layer_range: [0, 32]
    model: jsfs11/MoEv4Config-TestWeightedTIES-7b
  - layer_range: [0, 32]
    model: nlpguy/AlloyIngot
```

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "jsfs11/RandomMergeWEIGHTED-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"])
```