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---
tags:
- merge
- mergekit
- cognitivecomputations/dolphin-2.9-llama3-8b
- NousResearch/Hermes-2-Theta-Llama-3-8B
base_model:
- cognitivecomputations/dolphin-2.9-llama3-8b
- NousResearch/Hermes-2-Theta-Llama-3-8B
license: apache-2.0
---
![](https://raw.githubusercontent.com/saucam/models/main/proteus.png)
# 💧 Proteus-8B
Proteus-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-Theta-Llama-3-8B](https://huggingface.co/NousResearch/Hermes-2-Theta-Llama-3-8B)
## 🧩 Configuration
```yamltokenizer_source: union
tokenizer_source: union
embed_slerp: true
name: Proteus-8B
models:
- model: cognitivecomputations/dolphin-2.9-llama3-8b
parameters:
density: 0.5
weight: 0.4
- model: NousResearch/Hermes-2-Theta-Llama-3-8B
parameters:
density: 0.5
weight: 0.6
merge_method: dare_ties
base_model: NousResearch/Hermes-2-Theta-Llama-3-8B
parameters:
int8_mask: true
dtype: bfloat16
```
## Eval Results
| Benchmark | Average | arc | gsm8k | hellaswag | mmlu | truthfulqa | winogrande |
|-----------|---------:|----:|----:|---:|---------:|--------:|------:|
| openllm | 70.67 | 63.48 | 78.77 | 82.94 | 64.71 | 56.71 | 77.43 |
Detailed Results: https://github.com/saucam/model_evals/blob/main/saucam/Proteus-8B/README.md
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "saucam/Proteus-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"])
``` |