--- license: llama3.1 library_name: transformers tags: - moe - frankenmoe - merge - mergekit base_model: - Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base - ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.2 model-index: - name: L3.1-Moe-2x8B-v0.2 results: - task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics: - type: inst_level_strict_acc and prompt_level_strict_acc value: 73.48 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=moeru-ai/L3.1-Moe-2x8B-v0.2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics: - type: acc_norm value: 32.95 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=moeru-ai/L3.1-Moe-2x8B-v0.2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics: - type: exact_match value: 15.26 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=moeru-ai/L3.1-Moe-2x8B-v0.2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics: - type: acc_norm value: 6.71 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=moeru-ai/L3.1-Moe-2x8B-v0.2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics: - type: acc_norm value: 11.38 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=moeru-ai/L3.1-Moe-2x8B-v0.2 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 31.76 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=moeru-ai/L3.1-Moe-2x8B-v0.2 name: Open LLM Leaderboard --- # L3.1-Moe-2x8B-v0.2 ![cover](https://github.com/moeru-ai/L3.1-Moe/blob/main/cover/v0.2.png?raw=true) This model is a Mixture of Experts (MoE) made with mergekit-moe. It uses the following base models: - [Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base](https://huggingface.co/Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base) - [ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.2](https://huggingface.co/ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.2) Heavily inspired by [mlabonne/Beyonder-4x7B-v3](https://huggingface.co/mlabonne/Beyonder-4x7B-v3). ## Quantized models ### GGUF by [mradermacher](https://huggingface.co/mradermacher) - [mradermacher/L3.1-Moe-2x8B-v0.2-i1-GGUF](https://huggingface.co/mradermacher/L3.1-Moe-2x8B-v0.2-i1-GGUF) - [mradermacher/L3.1-Moe-2x8B-v0.2-GGUF](https://huggingface.co/mradermacher/L3.1-Moe-2x8B-v0.2-GGUF) ## Mergekit config
mergekit_moe_config.yml ```yaml base_model: Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base gate_mode: hidden dtype: bfloat16 experts: - source_model: Joseph717171/Llama-3.1-SuperNova-8B-Lite_TIES_with_Base positive_prompts: &common_prompts - "chat" - "assistant" - "tell me" - "explain" - "I want" - "code" - "python" - "javascript" - "programming" - "algorithm" - "reason" - "math" - "mathematics" - "solve" - "count" negative_prompts: &rp_prompts - "storywriting" - "write" - "scene" - "story" - "character" - source_model: ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.2 positive_prompts: *rp_prompts negative_prompts: *common_prompts ```
# [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/details_moeru-ai__L3.1-Moe-2x8B-v0.2) | Metric |Value| |-------------------|----:| |Avg. |28.59| |IFEval (0-Shot) |73.48| |BBH (3-Shot) |32.95| |MATH Lvl 5 (4-Shot)|15.26| |GPQA (0-shot) | 6.71| |MuSR (0-shot) |11.38| |MMLU-PRO (5-shot) |31.76|