--- tags: - merge - mergekit - lazymergekit - not-for-all-audiences - nsfw - rp - roleplay - role-play license: llama3 language: - en pipeline_tag: text-generation base_model: - Sao10K/L3-8B-Stheno-v3.2 - ChaoticNeutrals/Poppy_Porpoise-1.0-L3-8B - Nitral-AI/Hathor_Stable-v0.2-L3-8B - NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS - Hastagaras/Jamet-8B-L3-MK.V-Blackroot - openlynn/Llama-3-Soliloquy-8B-v2 - NousResearch/Meta-Llama-3-8B-Instruct - turboderp/llama3-turbcat-instruct-8b - VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct - TIGER-Lab/MAmmoTH2-8B-Plus - jondurbin/bagel-8b-v1.0 - abacusai/Llama-3-Smaug-8B - failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 - AwanLLM/Awanllm-Llama-3-8B-Cumulus-v1.0 - lodrick-the-lafted/Limon-8B - vicgalle/Configurable-Llama-3-8B-v0.3 - Undi95/Llama3-Unholy-8B-OAS - Undi95/Unholy-8B-DPO-OAS - WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0 - migtissera/Tess-2.0-Llama-3-8B - defog/llama-3-sqlcoder-8b - HPAI-BSC/Llama3-Aloe-8B-Alpha - maldv/llama-3-fantasy-writer-8b - lodrick-the-lafted/Olethros-8B - Magpie-Align/Llama-3-8B-ShareGPT-112K - Magpie-Align/Llama-3-8B-WildChat - Magpie-Align/Llama-3-8B-Tulu-330K - Magpie-Align/Llama-3-8B-OpenHermes-243K - Magpie-Align/Llama-3-8B-WizardLM-196K - Magpie-Align/Llama-3-8B-Ultrachat-200K - refuelai/Llama-3-Refueled - Danielbrdz/Barcenas-Llama3-8b-ORPO - migtissera/Llama-3-8B-Synthia-v3.5 - chujiezheng/Llama-3-Instruct-8B-SimPO-ExPO - chujiezheng/LLaMA3-iterative-DPO-final-ExPO - chargoddard/prometheus-2-llama-3-8b --- # L3-Deluxe-Scrambled-Eggs-On-Toast-8B **L3-Deluxe-Scrambled-Eggs-On-Toast-8B** is a role-play model merger **using 36 models** that was made **in 23 merging steps.** The goal is to create both a creative and smart model by using gradients. Each model has their own section in the gradient where they have a larger weight to promote intelligence whereas the rest of the models in the section of the gradient have a small weight to promote creativity. The following models were used as inspiration: * [grimjim/kunoichi-lemon-royale-v3-32K-7B](https://huggingface.co./grimjim/kunoichi-lemon-royale-v3-32K-7B) * [invisietch/EtherealRainbow-v0.3-8B](https://huggingface.co./invisietch/EtherealRainbow-v0.3-8B) * [PJMixers/LLaMa-3-CursedStock-v2.0-8B](https://huggingface.co./PJMixers/LLaMa-3-CursedStock-v2.0-8B) ## Instruct Format Llama 3 ## Settings/Presets ### Instruct/Context Virt-io's [SillyTavern Presets](https://huggingface.co./Virt-io/SillyTavern-Presets/tree/main/Prompts/LLAMA-3/v1.9) is recommended. ### Sampler Settings Here are the current recommended settings for **more creativity**. ```yaml Top K: 60 Min P: 0.035 Rep Pen: 1.05 Rep Pen Range: 2048 Pres Pen: 0.15 Smoothing Factor: 0.25 Dyna Temp: Min Temp: 0.75 Max Temp: 1.5 Expo: 0.85 ``` Here are the current recommended settings for **more adherencey**. Created by [**Dunjeon**!](https://huggingface.co./Casual-Autopsy/L3-Deluxe-Scrambled-Eggs-On-Toast-8B/discussions/2#66a8b7c87e658a8f072afb9d) ```yaml temperature: 0.7 top_p: 0.75 top_k: 30 min_p: 0.02 rep_pen: 1.1 rep_pen_range: 2048 presence_pen: 0.03 Smooth Sampling: smoothing_factor: 0.25 DRY: dry_allowed_length: 2 dry_multiplier: 0.8 dry_base: 1.75 dry_penalty_last_n: 4096 DynaTemp: dynatemp: false #found it better without, but you can flip it on and see how it goes min_temp: 0.7 max_temp: 0.9 dynatemp_exponent: 0.85 ``` ## Quants Weighted quants by: - [mradermacher](https://huggingface.co./mradermacher/L3-Deluxe-Scrambled-Eggs-On-Toast-8B-i1-GGUF) Static quants by: - [mradermacher](https://huggingface.co./mradermacher/L3-Deluxe-Scrambled-Eggs-On-Toast-8B-GGUF) # Secret Sauce ## Models Used L3-Scrambled-Eggs-On-Toast-8B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): * [Sao10K/L3-8B-Stheno-v3.2](https://huggingface.co./Sao10K/L3-8B-Stheno-v3.2) * [ChaoticNeutrals/Poppy_Porpoise-1.0-L3-8B](https://huggingface.co./ChaoticNeutrals/Poppy_Porpoise-1.0-L3-8B) * [Nitral-AI/Hathor_Stable-v0.2-L3-8B](https://huggingface.co./Nitral-AI/Hathor_Stable-v0.2-L3-8B) * [NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS](https://huggingface.co./NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS) * [Hastagaras/Jamet-8B-L3-MK.V-Blackroot](https://huggingface.co./Hastagaras/Jamet-8B-L3-MK.V-Blackroot) * [openlynn/Llama-3-Soliloquy-8B-v2](https://huggingface.co./openlynn/Llama-3-Soliloquy-8B-v2) * [NousResearch/Meta-Llama-3-8B-Instruct](https://huggingface.co./NousResearch/Meta-Llama-3-8B-Instruct) * [turboderp/llama3-turbcat-instruct-8b](https://huggingface.co./turboderp/llama3-turbcat-instruct-8b) * [VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct](https://huggingface.co./VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct) * [TIGER-Lab/MAmmoTH2-8B-Plus](https://huggingface.co./TIGER-Lab/MAmmoTH2-8B-Plus) * [jondurbin/bagel-8b-v1.0](https://huggingface.co./jondurbin/bagel-8b-v1.0) * [abacusai/Llama-3-Smaug-8B](https://huggingface.co./abacusai/Llama-3-Smaug-8B) * [failspy/Meta-Llama-3-8B-Instruct-abliterated-v3](https://huggingface.co./failspy/Meta-Llama-3-8B-Instruct-abliterated-v3) * [AwanLLM/Awanllm-Llama-3-8B-Cumulus-v1.0](https://huggingface.co./AwanLLM/Awanllm-Llama-3-8B-Cumulus-v1.0) * [lodrick-the-lafted/Limon-8B](https://huggingface.co./lodrick-the-lafted/Limon-8B) * [vicgalle/Configurable-Llama-3-8B-v0.3](https://huggingface.co./vicgalle/Configurable-Llama-3-8B-v0.3) * [Undi95/Llama3-Unholy-8B-OAS](https://huggingface.co./Undi95/Llama3-Unholy-8B-OAS) * [Undi95/Unholy-8B-DPO-OAS](https://huggingface.co./Undi95/Unholy-8B-DPO-OAS) * [WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0](https://huggingface.co./WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0) * [migtissera/Tess-2.0-Llama-3-8B](https://huggingface.co./migtissera/Tess-2.0-Llama-3-8B) * [defog/llama-3-sqlcoder-8b](https://huggingface.co./defog/llama-3-sqlcoder-8b) * [HPAI-BSC/Llama3-Aloe-8B-Alpha](https://huggingface.co./HPAI-BSC/Llama3-Aloe-8B-Alpha) * [maldv/llama-3-fantasy-writer-8b](https://huggingface.co./maldv/llama-3-fantasy-writer-8b) * [lodrick-the-lafted/Olethros-8B](https://huggingface.co./lodrick-the-lafted/Olethros-8B) * [Magpie-Align/Llama-3-8B-ShareGPT-112K](https://huggingface.co./Magpie-Align/Llama-3-8B-ShareGPT-112K) * [Magpie-Align/Llama-3-8B-WildChat](https://huggingface.co./Magpie-Align/Llama-3-8B-WildChat) * [Magpie-Align/Llama-3-8B-Tulu-330K](https://huggingface.co./Magpie-Align/Llama-3-8B-Tulu-330K) * [Magpie-Align/Llama-3-8B-OpenHermes-243K](https://huggingface.co./Magpie-Align/Llama-3-8B-OpenHermes-243K) * [Magpie-Align/Llama-3-8B-WizardLM-196K](https://huggingface.co./Magpie-Align/Llama-3-8B-WizardLM-196K) * [Magpie-Align/Llama-3-8B-Ultrachat-200K](https://huggingface.co./Magpie-Align/Llama-3-8B-Ultrachat-200K) * [refuelai/Llama-3-Refueled](https://huggingface.co./refuelai/Llama-3-Refueled) * [Danielbrdz/Barcenas-Llama3-8b-ORPO](https://huggingface.co./Danielbrdz/Barcenas-Llama3-8b-ORPO) * [migtissera/Llama-3-8B-Synthia-v3.5](https://huggingface.co./migtissera/Llama-3-8B-Synthia-v3.5) * [chujiezheng/Llama-3-Instruct-8B-SimPO-ExPO](https://huggingface.co./chujiezheng/Llama-3-Instruct-8B-SimPO-ExPO) * [chujiezheng/LLaMA3-iterative-DPO-final-ExPO](https://huggingface.co./chujiezheng/LLaMA3-iterative-DPO-final-ExPO) * [chargoddard/prometheus-2-llama-3-8b](https://huggingface.co./chargoddard/prometheus-2-llama-3-8b) ## YAML Configs Used The following YAML configs were used to make this mode ### Eggs-and-Bread-RP-pt.1 ```yaml models: - model: Sao10K/L3-8B-Stheno-v3.2 - model: ChaoticNeutrals/Poppy_Porpoise-1.0-L3-8B parameters: density: 0.5 weight: [0.33, 0.0825, 0.0825, 0.0825, 0.0825] - model: Nitral-AI/Hathor_Stable-v0.2-L3-8B parameters: density: 0.5 weight: [0.0825, 0.33, 0.0825, 0.0825, 0.0825] - model: NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS parameters: density: 0.5 weight: [0.0825, 0.0825, 0.33, 0.0825, 0.0825] - model: Hastagaras/Jamet-8B-L3-MK.V-Blackroot parameters: density: 0.5 weight: [0.0825, 0.0825, 0.0825, 0.33, 0.0825] - model: openlynn/Llama-3-Soliloquy-8B-v2 parameters: density: 0.5 weight: [0.0825, 0.0825, 0.0825, 0.0825, 0.33] merge_method: dare_ties base_model: Sao10K/L3-8B-Stheno-v3.2 parameters: normalize: false int8_mask: true dtype: bfloat16 ``` ### Eggs-and-Bread-RP-pt.2 ```yaml models: - model: Sao10K/L3-8B-Stheno-v3.2 - model: ChaoticNeutrals/Poppy_Porpoise-1.0-L3-8B parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.0825, 0.0825, 0.33] - model: Nitral-AI/Hathor_Stable-v0.2-L3-8B parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.0825, 0.33, 0.0825] - model: NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.33, 0.0825, 0.0825] - model: Hastagaras/Jamet-8B-L3-MK.V-Blackroot parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.33, 0.0825, 0.0825, 0.0825] - model: openlynn/Llama-3-Soliloquy-8B-v2 parameters: gamma: 0.01 density: 0.9 weight: [0.33, 0.0825, 0.0825, 0.0825, 0.0825] merge_method: breadcrumbs_ties base_model: Sao10K/L3-8B-Stheno-v3.2 parameters: normalize: false int8_mask: true dtype: bfloat16 ``` ### Egg-and-Bread-RP ```yaml models: - model: Casual-Autopsy/Eggs-and-Bread-RP-pt.1 - model: Casual-Autopsy/Eggs-and-Bread-RP-pt.2 merge_method: slerp base_model: Casual-Autopsy/Eggs-and-Bread-RP-pt.1 parameters: t: - filter: self_attn value: [0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5] - filter: mlp value: [0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5] - value: 0.5 dtype: bfloat16 ``` ### Eggs-and-Bread-IQ-pt.1 ```yaml models: - model: NousResearch/Meta-Llama-3-8B-Instruct - model: turboderp/llama3-turbcat-instruct-8b parameters: density: 0.5 weight: [0.33, 0.0825, 0.0825, 0.0825, 0.0825] - model: VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct parameters: density: 0.5 weight: [0.0825, 0.33, 0.0825, 0.0825, 0.0825] - model: TIGER-Lab/MAmmoTH2-8B-Plus parameters: density: 0.5 weight: [0.0825, 0.0825, 0.33, 0.0825, 0.0825] - model: jondurbin/bagel-8b-v1.0 parameters: density: 0.5 weight: [0.0825, 0.0825, 0.0825, 0.33, 0.0825] - model: abacusai/Llama-3-Smaug-8B parameters: density: 0.5 weight: [0.0825, 0.0825, 0.0825, 0.0825, 0.33] merge_method: dare_ties base_model: NousResearch/Meta-Llama-3-8B-Instruct parameters: normalize: false int8_mask: true dtype: bfloat16 ``` ### Eggs-and-Bread-IQ-pt.2 ```yaml models: - model: NousResearch/Meta-Llama-3-8B-Instruct - model: turboderp/llama3-turbcat-instruct-8b parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.0825, 0.0825, 0.33] - model: VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.0825, 0.33, 0.0825] - model: TIGER-Lab/MAmmoTH2-8B-Plus parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.33, 0.0825, 0.0825] - model: jondurbin/bagel-8b-v1.0 parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.33, 0.0825, 0.0825, 0.0825] - model: abacusai/Llama-3-Smaug-8B parameters: gamma: 0.01 density: 0.9 weight: [0.33, 0.0825, 0.0825, 0.0825, 0.0825] merge_method: breadcrumbs_ties base_model: NousResearch/Meta-Llama-3-8B-Instruct parameters: normalize: false int8_mask: true dtype: bfloat16 ``` ### Eggs-and-Bread-IQ ```yaml models: - model: Casual-Autopsy/Eggs-and-Bread-IQ-pt.1 - model: Casual-Autopsy/Eggs-and-Bread-IQ-pt.2 merge_method: slerp base_model: Casual-Autopsy/Eggs-and-Bread-IQ-pt.1 parameters: t: - filter: self_attn value: [0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5] - filter: mlp value: [0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5] - value: 0.5 dtype: bfloat16 ``` ### Eggs-and-Bread-Uncen-pt.1 ```yaml models: - model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 - model: AwanLLM/Awanllm-Llama-3-8B-Cumulus-v1.0 parameters: density: 0.5 weight: [0.33, 0.0825, 0.0825, 0.0825, 0.0825] - model: lodrick-the-lafted/Limon-8B parameters: density: 0.5 weight: [0.0825, 0.33, 0.0825, 0.0825, 0.0825] - model: vicgalle/Configurable-Llama-3-8B-v0.3 parameters: density: 0.5 weight: [0.0825, 0.0825, 0.33, 0.0825, 0.0825] - model: Undi95/Llama3-Unholy-8B-OAS parameters: density: 0.5 weight: [0.0825, 0.0825, 0.0825, 0.33, 0.0825] - model: Undi95/Unholy-8B-DPO-OAS parameters: density: 0.5 weight: [0.0825, 0.0825, 0.0825, 0.0825, 0.33] merge_method: dare_ties base_model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 parameters: normalize: false int8_mask: true dtype: bfloat16 ``` ### Eggs-and-Bread-Uncen-pt.2 ```yaml models: - model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 - model: AwanLLM/Awanllm-Llama-3-8B-Cumulus-v1.0 parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.0825, 0.0825, 0.33] - model: lodrick-the-lafted/Limon-8B parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.0825, 0.33, 0.0825] - model: vicgalle/Configurable-Llama-3-8B-v0.3 parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.33, 0.0825, 0.0825] - model: Undi95/Llama3-Unholy-8B-OAS parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.33, 0.0825, 0.0825, 0.0825] - model: Undi95/Unholy-8B-DPO-OAS parameters: gamma: 0.01 density: 0.9 weight: [0.33, 0.0825, 0.0825, 0.0825, 0.0825] merge_method: breadcrumbs_ties base_model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3 parameters: normalize: false int8_mask: true dtype: bfloat16 ``` ### Eggs-and-Bread-Uncen ```yaml models: - model: Casual-Autopsy/Eggs-and-Bread-Uncen-pt.1 - model: Casual-Autopsy/Eggs-and-Bread-Uncen-pt.2 merge_method: slerp base_model: Casual-Autopsy/Eggs-and-Bread-Uncen-pt.1 parameters: t: - filter: self_attn value: [0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5] - filter: mlp value: [0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5] - value: 0.5 dtype: bfloat16 ``` ### Scrambled-Eggs-On-Toast-1 ```yaml models: - model: Casual-Autopsy/Eggs-and-Bread-RP - model: Casual-Autopsy/Eggs-and-Bread-Uncen merge_method: slerp base_model: Casual-Autopsy/Eggs-and-Bread-RP parameters: t: - value: [0.1, 0.15, 0.2, 0.4, 0.6, 0.4, 0.2, 0.15, 0.1] dtype: bfloat16 ``` ### L3-Scrambled-Eggs-On-Toast-8B ```yaml models: - model: Casual-Autopsy/Scrambled-Eggs-On-Toast-1 - model: Casual-Autopsy/Eggs-and-Bread-IQ merge_method: slerp base_model: Casual-Autopsy/Scrambled-Eggs-On-Toast-1 parameters: t: - value: [0.7, 0.5, 0.3, 0.25, 0.2, 0.25, 0.3, 0.5, 0.7] dtype: bfloat16 ``` ### Eggs-and-Bread-Misc1-pt.1 ```yaml models: - model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0 - model: migtissera/Tess-2.0-Llama-3-8B parameters: density: 0.5 weight: [0.33, 0.0825, 0.0825, 0.0825, 0.0825] - model: defog/llama-3-sqlcoder-8b parameters: density: 0.5 weight: [0.0825, 0.33, 0.0825, 0.0825, 0.0825] - model: HPAI-BSC/Llama3-Aloe-8B-Alpha parameters: density: 0.5 weight: [0.0825, 0.0825, 0.33, 0.0825, 0.0825] - model: maldv/llama-3-fantasy-writer-8b parameters: density: 0.5 weight: [0.0825, 0.0825, 0.0825, 0.33, 0.0825] - model: lodrick-the-lafted/Olethros-8B parameters: density: 0.5 weight: [0.0825, 0.0825, 0.0825, 0.0825, 0.33] merge_method: dare_ties base_model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0 parameters: normalize: false int8_mask: true dtype: bfloat16 ``` ### Eggs-and-Bread-Misc1-pt.2 ```yaml models: - model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0 - model: migtissera/Tess-2.0-Llama-3-8B parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.0825, 0.0825, 0.33] - model: defog/llama-3-sqlcoder-8b parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.0825, 0.33, 0.0825] - model: HPAI-BSC/Llama3-Aloe-8B-Alpha parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.33, 0.0825, 0.0825] - model: maldv/llama-3-fantasy-writer-8b parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.33, 0.0825, 0.0825, 0.0825] - model: lodrick-the-lafted/Olethros-8B parameters: gamma: 0.01 density: 0.9 weight: [0.33, 0.0825, 0.0825, 0.0825, 0.0825] merge_method: breadcrumbs_ties base_model: WhiteRabbitNeo/Llama-3-WhiteRabbitNeo-8B-v2.0 parameters: normalize: false int8_mask: true dtype: bfloat16 ``` ### Eggs-and-Bread-Misc1 ```yaml models: - model: Casual-Autopsy/Eggs-and-Bread-Misc1-pt.1 - model: Casual-Autopsy/Eggs-and-Bread-Misc1-pt.2 merge_method: slerp base_model: Casual-Autopsy/Eggs-and-Bread-Misc1-pt.1 parameters: t: - filter: self_attn value: [0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5] - filter: mlp value: [0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5] - value: 0.5 dtype: bfloat16 ``` ### Eggs-and-Bread-FFT-pt.1 ```yaml models: - model: Magpie-Align/Llama-3-8B-ShareGPT-112K - model: Magpie-Align/Llama-3-8B-WildChat parameters: density: 0.5 weight: [0.33, 0.0825, 0.0825, 0.0825, 0.0825] - model: Magpie-Align/Llama-3-8B-Tulu-330K parameters: density: 0.5 weight: [0.0825, 0.33, 0.0825, 0.0825, 0.0825] - model: Magpie-Align/Llama-3-8B-OpenHermes-243K parameters: density: 0.5 weight: [0.0825, 0.0825, 0.33, 0.0825, 0.0825] - model: Magpie-Align/Llama-3-8B-WizardLM-196K parameters: density: 0.5 weight: [0.0825, 0.0825, 0.0825, 0.33, 0.0825] - model: Magpie-Align/Llama-3-8B-Ultrachat-200K parameters: density: 0.5 weight: [0.0825, 0.0825, 0.0825, 0.0825, 0.33] merge_method: dare_ties base_model: Magpie-Align/Llama-3-8B-ShareGPT-112K parameters: normalize: false int8_mask: true dtype: bfloat16 ``` ### Eggs-and-Bread-FFT-pt.2 ```yaml models: - model: Magpie-Align/Llama-3-8B-ShareGPT-112K - model: Magpie-Align/Llama-3-8B-WildChat parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.0825, 0.0825, 0.33] - model: Magpie-Align/Llama-3-8B-Tulu-330K parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.0825, 0.33, 0.0825] - model: Magpie-Align/Llama-3-8B-OpenHermes-243K parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.33, 0.0825, 0.0825] - model: Magpie-Align/Llama-3-8B-WizardLM-196K parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.33, 0.0825, 0.0825, 0.0825] - model: Magpie-Align/Llama-3-8B-Ultrachat-200K parameters: gamma: 0.01 density: 0.9 weight: [0.33, 0.0825, 0.0825, 0.0825, 0.0825] merge_method: breadcrumbs_ties base_model: Magpie-Align/Llama-3-8B-ShareGPT-112K parameters: normalize: false int8_mask: true dtype: bfloat16 ``` ### Eggs-and-Bread-FFT ```yaml models: - model: Casual-Autopsy/Eggs-and-Bread-FFT-pt.1 - model: Casual-Autopsy/Eggs-and-Bread-FFT-pt.2 merge_method: slerp base_model: Casual-Autopsy/Eggs-and-Bread-FFT-pt.1 parameters: t: - filter: self_attn value: [0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5] - filter: mlp value: [0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5] - value: 0.5 dtype: bfloat16 ``` ### Eggs-and-Bread-Misc2-pt.1 ```yaml models: - model: refuelai/Llama-3-Refueled - model: Danielbrdz/Barcenas-Llama3-8b-ORPO parameters: density: 0.5 weight: [0.33, 0.0825, 0.0825, 0.0825, 0.0825] - model: migtissera/Llama-3-8B-Synthia-v3.5 parameters: density: 0.5 weight: [0.0825, 0.33, 0.0825, 0.0825, 0.0825] - model: chujiezheng/Llama-3-Instruct-8B-SimPO-ExPO parameters: density: 0.5 weight: [0.0825, 0.0825, 0.33, 0.0825, 0.0825] - model: chujiezheng/LLaMA3-iterative-DPO-final-ExPO parameters: density: 0.5 weight: [0.0825, 0.0825, 0.0825, 0.33, 0.0825] - model: chargoddard/prometheus-2-llama-3-8b parameters: density: 0.5 weight: [0.0825, 0.0825, 0.0825, 0.0825, 0.33] merge_method: dare_ties base_model: refuelai/Llama-3-Refueled parameters: normalize: false int8_mask: true dtype: bfloat16 ``` ### Eggs-and-Bread-Misc2-pt.2 ```yaml models: - model: refuelai/Llama-3-Refueled - model: Danielbrdz/Barcenas-Llama3-8b-ORPO parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.0825, 0.0825, 0.33] - model: migtissera/Llama-3-8B-Synthia-v3.5 parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.0825, 0.33, 0.0825] - model: chujiezheng/Llama-3-Instruct-8B-SimPO-ExPO parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.0825, 0.33, 0.0825, 0.0825] - model: chujiezheng/LLaMA3-iterative-DPO-final-ExPO parameters: gamma: 0.01 density: 0.9 weight: [0.0825, 0.33, 0.0825, 0.0825, 0.0825] - model: chargoddard/prometheus-2-llama-3-8b parameters: gamma: 0.01 density: 0.9 weight: [0.33, 0.0825, 0.0825, 0.0825, 0.0825] merge_method: breadcrumbs_ties base_model: refuelai/Llama-3-Refueled parameters: normalize: false int8_mask: true dtype: bfloat16 ``` ### Eggs-and-Bread-Misc2 ```yaml models: - model: Casual-Autopsy/Eggs-and-Bread-Misc2-pt.1 - model: Casual-Autopsy/Eggs-and-Bread-Misc2-pt.2 merge_method: slerp base_model: Casual-Autopsy/Eggs-and-Bread-Misc2-pt.1 parameters: t: - filter: self_attn value: [0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5] - filter: mlp value: [0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5, 0.7, 0.3, 0.5, 0.3, 0.7, 0.5] - value: 0.5 dtype: bfloat16 ``` ### Scrambled-Eggs-On-Toast-2 ```yaml models: - model: Casual-Autopsy/Eggs-and-Bread-Misc1 - model: Casual-Autopsy/Eggs-and-Bread-Misc2 merge_method: slerp base_model: Casual-Autopsy/Eggs-and-Bread-Misc1 parameters: t: - value: [0.1, 0.15, 0.2, 0.4, 0.6, 0.4, 0.2, 0.15, 0.1] dtype: bfloat16 ``` ### Scrambled-Eggs-On-Toast-3 ```yaml models: - model: Casual-Autopsy/Scrambled-Eggs-On-Toast-2 - model: Casual-Autopsy/Eggs-and-Bread-FFT merge_method: slerp base_model: Casual-Autopsy/Scrambled-Eggs-On-Toast-2 parameters: t: - value: [0.7, 0.5, 0.3, 0.25, 0.2, 0.25, 0.3, 0.5, 0.7] dtype: bfloat16 ``` ### L3-Deluxe-Scrambled-Eggs-On-Toast-8B ```yaml models: - model: Casual-Autopsy/L3-Scrambled-Eggs-On-Toast-8B - model: Casual-Autopsy/Scrambled-Eggs-On-Toast-3 merge_method: slerp base_model: Casual-Autopsy/L3-Scrambled-Eggs-On-Toast-8B parameters: t: - value: [0.2, 0.25, 0.3, 0.4, 0.3, 0.25, 0.2, 0.25, 0.3, 0.4, 0.3, 0.25, 0.2] dtype: bfloat16 ```