--- library_name: transformers tags: - mergekit - merge base_model: - akjindal53244/Llama-3.1-Storm-8B - Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2 - arcee-ai/Llama-3.1-SuperNova-Lite - unsloth/Meta-Llama-3.1-8B-Instruct model-index: - name: ZEUS-8B-V10 results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: wis-k/instruction-following-eval split: train args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 77.07 name: averaged accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V10 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: SaylorTwift/bbh split: test args: num_few_shot: 3 metrics: - type: acc_norm value: 32.7 name: normalized accuracy source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V10 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: lighteval/MATH-Hard split: test args: num_few_shot: 4 metrics: - type: exact_match value: 20.09 name: exact match source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V10 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa split: train args: num_few_shot: 0 metrics: - type: acc_norm value: 9.96 name: acc_norm source: url: >- https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/?search=T145%2FZEUS-8B-V10 name: Open LLM Leaderboard new_version: T145/ZEUS-8B-V13 --- # ZEUS 8B 🌩️ V10 A V2 recreation with a few changes: * Unified tokenizer (no noticeable changes) * Using `int_mask` and `normalize` (the latter being enabled by default in mergekit) * Using a preset seed to create a reproducible config (due to DARE relying on RNG) Expecting little to no change over V2. ## 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 [unsloth/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/unsloth/Meta-Llama-3.1-8B-Instruct) as a base. ### Models Merged The following models were included in the merge: * [akjindal53244/Llama-3.1-Storm-8B](https://huggingface.co/akjindal53244/Llama-3.1-Storm-8B) * [Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2](https://huggingface.co/Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2) * [arcee-ai/Llama-3.1-SuperNova-Lite](https://huggingface.co/arcee-ai/Llama-3.1-SuperNova-Lite) ### Configuration The following YAML configuration was used to produce this model: ```yaml base_model: unsloth/Meta-Llama-3.1-8B-Instruct dtype: bfloat16 merge_method: dare_ties parameters: int8_mask: 1.0 normalize: 1.0 random_seed: 42.0 slices: - sources: - layer_range: [0, 32] model: akjindal53244/Llama-3.1-Storm-8B parameters: density: 0.8 weight: 0.25 - layer_range: [0, 32] model: arcee-ai/Llama-3.1-SuperNova-Lite parameters: density: 0.8 weight: 0.33 - layer_range: [0, 32] model: Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2 parameters: density: 0.8 weight: 0.42 - layer_range: [0, 32] model: unsloth/Meta-Llama-3.1-8B-Instruct tokenizer_source: union ``` # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/T145__ZEUS-8B-V10-details)! Summarized results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/contents/viewer/default/train?q=T145/ZEUS-8B-V10)! | Metric |Value (%)| |-------------------|--------:| |**Average** | 30.19| |IFEval (0-Shot) | 77.07| |BBH (3-Shot) | 32.70| |MATH Lvl 5 (4-Shot)| 20.09| |GPQA (0-shot) | 9.96| |MuSR (0-shot) | 9.09| |MMLU-PRO (5-shot) | 32.26| ## Changes over V2 | Metric |Change| |-------------------|-----:| |Avg. |+0.12| |IFEval (0-Shot) |-3.22| |BBH (3-Shot) |+1.09| |MATH Lvl 5 (4-Shot)|-1.06| |GPQA (0-shot) |+3.02| |MuSR (0-shot) |+0.85| |MMLU-PRO (5-shot) |+0.08|