π¦ aqua-smaug-0.3-8B π
aqua-smaug-0.3-8B is a merge of the following models using Mergekit:
𧩠Configuration
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 | 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
π» Usage
!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%|βββββββββββββββββββββββββββββββββββββββββββββββββββ| 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. π
### References
- [Carnival Booth Earnings Calculation](https://www.calculator.net/calculators/math/equation-calculator.html) (for verifying calculations)
- [Cotton Candy
- Downloads last month
- 234
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for saucam/aqua-smaug-0.3-8B
Merge model
this model