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---
tags:
- merge
- mergekit
- cognitivecomputations/dolphin-2.9-llama3-8b
- NousResearch/Hermes-2-Pro-Llama-3-8B
- abacusai/Llama-3-Smaug-8B
base_model:
- cognitivecomputations/dolphin-2.9-llama3-8b
- NousResearch/Hermes-2-Pro-Llama-3-8B
- abacusai/Llama-3-Smaug-8B
license: apache-2.0
---
# aqua-smaug-hermes-8B
aqua-smaug-hermes-8B is a merge of the following models using [Mergekit](https://github.com/arcee-ai/mergekit):
* [cognitivecomputations/dolphin-2.9-llama3-8b](https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b)
* [NousResearch/Hermes-2-Pro-Llama-3-8B](https://huggingface.co/NousResearch/Hermes-2-Pro-Llama-3-8B)
* [abacusai/Llama-3-Smaug-8B](https://huggingface.co/abacusai/Llama-3-Smaug-8B)
## 🧩 Configuration
```yamlname: aqua-smaug-hermes-8B
tokenizer_source: union
base_model:
model:
path: NousResearch/Hermes-2-Pro-Llama-3-8B
dtype: float16
merge_method: dare_linear
parameters:
normalize: 1.0
slices:
- sources:
- model: cognitivecomputations/dolphin-2.9-llama3-8b
layer_range: [0, 32]
parameters:
weight: 0.3
- model: NousResearch/Hermes-2-Pro-Llama-3-8B
layer_range: [0, 32]
parameters:
weight: 0.4
- model: abacusai/Llama-3-Smaug-8B
layer_range: [0, 32]
parameters:
weight: 0.3
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "saucam/aqua-smaug-hermes-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"])
``` |