--- library_name: transformers tags: - llama-factory - merge license: llama3 language: - en --- # Model Card for Model ID ![image/webp](https://cdn-uploads.huggingface.co/production/uploads/643eab4f05a395e2b1c727e3/TciPHbHULFVgClbNaw0hY.webp) This is a fine tune of a merged model using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [cognitivecomputations/dolphin-2.9-llama3-8b](https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b) as a base. The following models were included in the merge: * [Weyaxi/Einstein-v6.1-Llama3-8B](https://huggingface.co/Weyaxi/Einstein-v6.1-Llama3-8B) ## Model Details Quant [Q8_0 GGUF](https://huggingface.co/giannisan/penny5-dolphin-einstein-llama3-dare-ties-chatml.gguf) ### Model Description This is the model card of a 🤗 transformers model that has been pushed on the Hub. - **Developed by:** [Gianni Sanrochman](https://x.com/Giannisanii) - **Funded by:** [Merildo Sanrochman] - **Model type:** [LLaMA-3](https://ai.meta.com/blog/meta-llama-3) - **Language(s) (NLP):** [English] - **License:** [llama3](https://huggingface.co/meta-llama/Meta-Llama-3-8B/blob/main/LICENSE) - **Finetuned from model:** [giannisan/dolphin-einstein-llama3-dare-ties](https://huggingface.co/giannisan/dolphin-einstein-llama3-dare-ties) using the PENNY dataset ## Training Details ### Training Data [More Information Needed] ### Training Procedure #### Training Hyperparameters - **Training regime:** [More Information Needed] #### Speeds, Sizes, Times [optional] [More Information Needed] ## Evaluation | Metric | Value | |----------------------|---------| | Avg. | 66.72 | | ARC (25-shot) | 61.01 | | HellaSwag (10-shot) | 82.50 | | MMLU (5-shot) | 64.48 | | TruthfulQA (0-shot) | 50.73 | | Winogrande (5-shot) | 74.11 | | GSM8K (5-shot) | 67.48 | full results [here](https://huggingface.co/datasets/open-llm-leaderboard/details_giannisan__penny5-dolphin-einstein-llama3-dare-ties-chatml/blob/main/results_2024-05-30T05-14-11.958453.json) ## Environmental Impact Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - **Hardware Type:** [Nvidia RTX A100] - **Hours used:** [2] - **Cloud Provider:** [RunPod] - **Compute Region:** [Europe] - **Carbon Emitted:** [More Information Needed] ## Model Card Authors [optional] [Gianni Sanrochman] ## Model Card Contact [More Information Needed]