README.md

---
tags:
- merge
- mergekit
- cognitivecomputations/dolphin-2.9-llama3-8b
- abacusai/Llama-3-Smaug-8B
- meta-llama/Meta-Llama-3-8B
base_model:
- cognitivecomputations/dolphin-2.9-llama3-8b
- abacusai/Llama-3-Smaug-8B
- meta-llama/Meta-Llama-3-8B
license: apache-2.0
---

![](https://raw.githubusercontent.com/saucam/models/main/aqua-smaug.png)

# 💦 aqua-smaug-0.3-8B 🐉

aqua-smaug-0.3-8B 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)
* [abacusai/Llama-3-Smaug-8B](https://huggingface.co/abacusai/Llama-3-Smaug-8B)
* [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B)

## 🧩 Configuration

```yamlname: aqua-smaug-0.3-8B
models:
  - model: cognitivecomputations/dolphin-2.9-llama3-8b
  - model: abacusai/Llama-3-Smaug-8B
  - model: meta-llama/Meta-Llama-3-8B
merge_method: model_stock
base_model: abacusai/Llama-3-Smaug-8B
dtype: bfloat16
```

## Eval Results

 |Benchmark|                               Model                                |winogrande| arc |gsm8k|mmlu|truthfulqa|hellaswag|Average|
|---------|--------------------------------------------------------------------|---------:|----:|----:|---:|---------:|--------:|------:|
|openllm  |[aqua-smaug-0.3-8B](https://huggingface.co/saucam/aqua-smaug-0.3-8B)|     77.11|62.37|76.19|  66|      53.7|    83.02|  69.73|

Detailed Results: https://github.com/saucam/model_evals/tree/main/saucam/aqua-smaug-0.3-8B

## 💻 Usage

```python
!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "saucam/aqua-smaug-0.3-8B"
messages = [{"role": "user", "content": "A carnival snack booth made $50 selling popcorn each day. It made three times as much selling cotton candy. For a 5-day activity, the booth has to pay $30 rent and $75 for the cost of the ingredients. How much did the booth earn for 5 days after paying the rent and the cost of ingredients? How much did the booth make selling cotton candy each day?"}]

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"])
```

output

```
Loading checkpoint shards: 100%|███████████████████████████████████████████████████| 2/2 [00:27<00:00, 13.83s/it]
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
<|begin_of_text|><|start_header_id|>user<|end_header_id|>

A carnival snack booth made $50 selling popcorn each day. It made three times as much selling cotton candy. For a 5-day activity, the booth has to pay $30 rent and $75 for the cost of the ingredients. How much did the booth earn for 5 days after paying the rent and the cost of ingredients? How much did the booth make selling cotton candy each day?<|eot_id|><|start_header_id|>assistant<|end_header_id|>

The carnival snack booth made $50 selling popcorn each day. Since it made three times as much selling cotton candy, it made $50 * 3 = $150 each day selling cotton candy.

For a 5-day activity, the booth made $50 * 5 = $250 selling popcorn and $150 * 5 = $750 selling cotton candy.

The booth has to pay $30 rent and $75 for the cost of the ingredients for 5 days, which is a total of $30 + $75 = $105.

After paying the rent and the cost of ingredients, the booth earned $250 + $750 - $105 = $895 for 5 days.

Therefore, the booth made $150 each day selling cotton candy. 

So, the total amount earned by selling popcorn is $250 and by selling cotton candy is $750. After deducting the rent and cost of ingredients, the booth earned a total of $895 for the 5-day activity. 

Hope this helps! Let me know if you have any more questions. 😊

### References
- [Carnival Booth Earnings Calculation](https://www.calculator.net/calculators/math/equation-calculator.html) (for verifying calculations) 
- [Cotton Candy

```