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L3 Deluxe Scrambled Eggs On Toast 8B GGUF
模型概述
該模型通過合併多個Llama-3變體模型，專注於角色扮演任務，旨在平衡創造力和智能表現。使用梯度方法優化模型權重分配，核心模型權重區域提升智能，其餘部分增強創造力。
模型特點
多模型融合
整合36個不同模型優勢，經過23個合併步驟優化
智能-創造力平衡
通過梯度方法分配權重，核心區域提升智能，外圍權重增強創造力
角色扮演優化
專為角色扮演場景設計，推薦使用SillyTavern預設
模型能力
角色扮演對話生成
創意文本寫作
指令跟隨
長上下文處理（推薦2048 tokens）
使用案例
娛樂
互動式角色扮演
與AI角色進行沉浸式對話互動
可生成符合角色設定的自然響應
創意寫作
故事生成
輔助創作者進行幻想文學創作
提供富有想象力的敘事內容
🚀 QuantFactory/L3-Deluxe-Scrambled-Eggs-On-Toast-8B-GGUF
這是使用llama.cpp創建的Casual-Autopsy/L3-Deluxe-Scrambled-Eggs-On-Toast-8B的量化版本。該項目旨在通過合併多個模型，打造一個兼具創造力和智能的角色扮演模型。
🚀 快速開始
本項目是一個基於多個模型合併的角色扮演模型，你可以參考以下內容瞭解模型的詳細信息。
✨ 主要特性
- 多模型融合：使用了36個模型，經過23個合併步驟，融合多個模型的優勢。
- 創造力與智能兼具：通過梯度方法，使模型既具有創造力，又具備較高的智能水平。
📚 詳細文檔
原始模型卡片
L3-Deluxe-Scrambled-Eggs-On-Toast-8B
L3-Deluxe-Scrambled-Eggs-On-Toast-8B 是一個角色扮演模型，它使用了36個模型，經過23個合併步驟得到。目標是通過梯度方法創建一個既具有創造力又智能的模型。每個模型在梯度中有自己的權重區域，以提升智能，而梯度中其餘模型的權重較小，以促進創造力。
以下模型作為靈感來源：
- grimjim/kunoichi-lemon-royale-v3-32K-7B
- invisietch/EtherealRainbow-v0.3-8B
- PJMixers/LLaMa-3-CursedStock-v2.0-8B
指令格式
Llama 3
設置/預設
指令/上下文
推薦使用Virt-io的 SillyTavern Presets。
採樣器設置
以下是當前推薦的設置，以獲得更多創造力：
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
目前沒有已知的用於更高遵循度的預設。如果你有相關預設，歡迎推薦！
量化
- 加權量化：由 mradermacher 完成。
- 靜態量化：由 mradermacher 完成。
秘製配方
使用的模型
L3-Scrambled-Eggs-On-Toast-8B 是使用 LazyMergekit 合併以下模型得到的：
- 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
使用的YAML配置
以下是用於創建此模型的YAML配置：
Eggs-and-Bread-RP-pt.1
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
models:
- model: refuelai/Llama-3-Refueled
- model: Danielbrdz/Barcenas-Llama3-8b-ORPO
parameters:
density: 0.5
# 原文檔此處未完整，保持原樣
📄 許可證
本項目採用llama3許可證。
信息表格
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