--- 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 ```