pp_merge-8B / README.md
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---
base_model:
- NousResearch/Hermes-2-Pro-Llama-3-8B
- meta-llama/Meta-Llama-3-8B-Instruct
tags:
- merge
- mergekit
- lazymergekit
- NousResearch/Hermes-2-Pro-Llama-3-8B
- meta-llama/Meta-Llama-3-8B-Instruct
---
# pp_merge-8B
pp_merge-8B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [NousResearch/Hermes-2-Pro-Llama-3-8B](https://huggingface.co/NousResearch/Hermes-2-Pro-Llama-3-8B)
* [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct)
## 🧩 Configuration
```yaml
slices:
- sources:
- model: NousResearch/Hermes-2-Pro-Llama-3-8B
layer_range:
- 0
- 32
- model: meta-llama/Meta-Llama-3-8B-Instruct
layer_range:
- 0
- 32
merge_method: slerp
base_model: meta-llama/Meta-Llama-3-8B-Instruct
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: bfloat16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "pawan2411/pp_merge-8B"
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"])
```