--- license: llama3 library_name: transformers tags: - mergekit - merge base_model: - Dampfinchen/Llama-3-8B-Ultra-Instruct - NousResearch/Meta-Llama-3-8B - NousResearch/Meta-Llama-3-8B-Instruct model-index: - name: Llama-3-8B-Ultra-Instruct-SaltSprinkle results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 61.35 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Dampfinchen/Llama-3-8B-Ultra-Instruct-SaltSprinkle name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 77.76 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Dampfinchen/Llama-3-8B-Ultra-Instruct-SaltSprinkle name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 67.88 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Dampfinchen/Llama-3-8B-Ultra-Instruct-SaltSprinkle name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 52.82 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Dampfinchen/Llama-3-8B-Ultra-Instruct-SaltSprinkle name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 74.98 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Dampfinchen/Llama-3-8B-Ultra-Instruct-SaltSprinkle name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 70.89 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Dampfinchen/Llama-3-8B-Ultra-Instruct-SaltSprinkle name: Open LLM Leaderboard --- # merge This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). ## Merge Details ### Merge Method This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [NousResearch/Meta-Llama-3-8B](https://huggingface.co/NousResearch/Meta-Llama-3-8B) as a base. ### Models Merged The following models were included in the merge: * [Dampfinchen/Llama-3-8B-Ultra-Instruct](https://huggingface.co/Dampfinchen/Llama-3-8B-Ultra-Instruct) * [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3-8B-Instruct) ### Configuration The following YAML configuration was used to produce this model: ```yaml models: - model: NousResearch/Meta-Llama-3-8B-Instruct parameters: density: 1 weight: 1 - model: Dampfinchen/Llama-3-8B-Ultra-Instruct parameters: density: 0.5 weight: 0.2 merge_method: dare_ties base_model: NousResearch/Meta-Llama-3-8B dtype: bfloat16 ``` Test of salt sprinkle methode. The goal is to retain all of L3 Instruct's capabilities while adding better RP, RAG, German and story writing capabilities in the form of Ultra Instruct. Model may generate harmful responses, I'm not responsible for what you do with this model. # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Dampfinchen__Llama-3-8B-Ultra-Instruct-SaltSprinkle) | Metric |Value| |---------------------------------|----:| |Avg. |67.61| |AI2 Reasoning Challenge (25-Shot)|61.35| |HellaSwag (10-Shot) |77.76| |MMLU (5-Shot) |67.88| |TruthfulQA (0-shot) |52.82| |Winogrande (5-shot) |74.98| |GSM8k (5-shot) |70.89|