--- license: cc-by-nc-4.0 tags: - not-for-all-audiences - nsfw --- First : ```shell layer_slices: - model: Undi95/MLewd-L2-Chat-13B start: 0 end: 16 - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1 start: 8 end: 20 - model: Undi95/MLewd-L2-Chat-13B start: 17 end: 32 - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1 start: 21 end: 40 ``` Inverted: ```shell layer_slices: - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1 start: 0 end: 16 - model: Undi95/MLewd-L2-Chat-13B start: 8 end: 20 - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1 start: 17 end: 32 - model: Undi95/MLewd-L2-Chat-13B start: 21 end: 40 ``` Precise: ```shell layer_slices: - model: Undi95/MLewd-L2-Chat-13B start: 0 end: 8 - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1 start: 4 end: 12 - model: Undi95/MLewd-L2-Chat-13B start: 9 end: 16 - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1 start: 13 end: 22 - model: Undi95/MLewd-L2-Chat-13B start: 17 end: 24 - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1 start: 23 end: 32 - model: Undi95/MLewd-L2-Chat-13B start: 25 end: 32 - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1 start: 33 end: 40 ``` PreciseInverted: ```shell layer_slices: - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1 start: 0 end: 8 - model: Undi95/MLewd-L2-Chat-13B start: 4 end: 12 - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1 start: 9 end: 16 - model: Undi95/MLewd-L2-Chat-13B start: 13 end: 22 - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1 start: 17 end: 24 - model: Undi95/MLewd-L2-Chat-13B start: 23 end: 32 - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1 start: 25 end: 32 - model: Undi95/MLewd-L2-Chat-13B start: 33 end: 40 ``` Part1 = ReMM v2.1 merged /w MLewd low weight to keep consistency. I call this "dilution" and result show consistency and coherency without repeat/loop beside the small amount of duplicated datas. The goal is to find the best way to interlace layers the best way possible to have a sweetspot between 13B and +30B. Normal/Inverted is by chunk of 16 layers and Precise/PreciseInverted is by chunk of 8 layers. All the models are made of 64(+1) layers. Need testing. ## Prompt template: Alpaca ``` Below is an instruction that describes a task. Write a response that completes the request. ### Instruction: {prompt} ### Response: ``` # [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_Undi95__MLewd-ReMM-L2-Chat-20B-Inverted) | Metric | Value | |-----------------------|---------------------------| | Avg. | 50.81 | | ARC (25-shot) | 61.69 | | HellaSwag (10-shot) | 85.32 | | MMLU (5-shot) | 58.0 | | TruthfulQA (0-shot) | 53.77 | | Winogrande (5-shot) | 75.61 | | GSM8K (5-shot) | 9.1 | | DROP (3-shot) | 12.16 |