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H3 Fight Flow V1 | Continuous Fight Interaction LoRA

8231°
H3 Fight Flow V1 | Continuous Fight Interaction LoRA
Created by
FourBunny
on Civitai
by FourBunny - H3 Fight Flow V1 | Continuous Fight Interaction LoRA - Fight Flow V1 does not mainly teach new moves. It explores whether H3 can learn how two or more characters should actually fight together.
Creator notes
Experimental Continuous Fight Interaction LoRA 实验性连续战斗交互增强 LoRA My goal is simple: push H3 from “can fight” to “knows how to fight.” 我的目标很简单:让 H3 从“能打”,变成真正“会打”。 🚀 Run It on RunningHub 🎁 New users on RunningHub International can get 1000 RH Coins after registration. 国内用户可以使用: What is this? 这是干什么的? Fight Flow V1 does not mainly teach new moves. It explores whether H3 can learn how two or more characters should actually fight together. Fight Flow V1 主要不是教 H3 更多招式,而是在实验:能不能让两个或多个人真正围绕同一场战斗进行互动。 Initiation → response → contact → consequence → initiative shift → next action. 发起 → 回应 → 接触 → 结果 → 主动权转换 → 下一动作继承。 The previous action should create the starting state of the next one, instead of constantly resetting back to a neutral pose. 上一招产生的位置、重心、距离和姿态,应该成为下一招的起点,而不是打一轮就重新摆架势。 D-OPSD Trained D-OPSD 训练版本 Unlike regular LoRA training that mainly relies on captions, D-OPSD allows the Teacher to directly reference the target training video. 不同于主要依赖 Caption 的普通 LoRA,D-OPSD 训练时 Teacher 可以直接参考目标训练视频。 This helps learn motion relationships that are difficult to fully describe with text: contact, trajectory, forced movement, weapon interaction, initiative changes and state transitions. 这样可以学习很多文字难以完整描述的内容,例如接触、轨迹、被动位移、武器交互、主动权变化和动作状态继承。 This V1 was trained entirely on RTX 6000D, with VRAM peaks around 60GB and roughly 2–3× my usual LoRA training time. 这一版全程使用 RTX 6000D 训练,显存峰值约 60GB,整体训练时间大约是我平常 LoRA 的 2~3 倍。 What does it improve? 它主要增强什么? Better attack-response causality, more natural initiative changes, stronger state continuity, and fewer “attack → reset → attack again” sequences. 攻击与回应的因果更完整,主动权转换更自然,状态继承更明显,也更少出现“打一招 → 重置 → 再打一招”。 In multi-person fights, one opponent can leave the exchange while another enters, instead of everyone simply performing independent actions at the same time. 在多人战中,当前敌人退出、主角换位、下一名敌人接入的衔接也会更加自然,而不是所有人同时各打各的。 Even with only a short prompt + trigger, the LoRA can already organize fairly complete combat exchanges by itself. 目前测试中,即使只使用一句简单 Prompt + 触发词,也已经能够自行组织出比较完整的连续战斗。 It is NOT a speed LoRA 它不是“加速 LoRA” The improvement is not simply “make both characters move faster.” It is mainly about how motion is organized and passed from one action into the next. 它并不是简单把两个人加速,让画面看起来更激烈;真正增强的是动作如何被组织,以及上一动作如何把状态传递给下一动作。 Three interaction triggers 三大交互触发词 - Unarmed combat interaction. — Use when punches, kicks, grappling, throws or body control dominate the fight. Unarmed combat interaction. —— 拳脚、摔投、身体控制等徒手交互主导时使用。 - Melee weapon interaction. — Use when blades, staffs, spears or other melee weapon lines dominate the exchange. Melee weapon interaction. —— 刀、剑、棍、枪等近战武器的攻击线、格挡和兵器接触主导时使用。 - Gun-fu interaction. — Use when muzzle control, firearm handling, close-range shooting or gun-hand interaction dominates the fight. Gun-fu interaction. —— 枪口控制、控枪、近距离射击和枪械近战交互主导时使用。 Choose the trigger by the dominant interaction logic, not simply by what equipment appears on screen. 判断时看整段战斗由什么交互逻辑主导,而不是单纯看角色手里拿了什么。 Body / fists → Unarmed | Melee weapon line → Melee Weapon | Muzzle / firearm control → Gun-fu 身体 / 拳脚主导 → 徒手|近战武器线主导 → Weapon|枪口与枪械控制主导 → GunFu Recommended use 推荐使用方式 Fight Flow works as an interaction layer together with Combat, Weapon and Motion Repair LoRAs. Fight Flow 更适合作为交互层,与 Combat、Weapon、GunFu、Motion Repair 等 LoRA 组合使用。 Specialized LoRAs decide what moves the characters know. Fight Flow helps those moves become one continuous fight. 专项 LoRA 决定角色会什么动作,Fight Flow 负责让这些动作真正连接成一场战斗。 Current tested weight: 0.65 in the first pass / 0.25 in the second pass. 当前测试权重:一采 0.65 / 二采 0.25。 Before: two characters are both fighting. 以前:两个人都在打。 Fight Flow V1: they are fighting the same fight. Fight Flow V1:两个人开始真正打同一场架。
Trigger words
Unarmed combat interaction
Melee weapon interaction,
Gun-fu interaction
740 downloads · 62 likes on Civitai
SHA256
579E8ECA67B6D70F4DB94B2DB67CD938751D576EE3D72ABA875DAE3D911F7398
Ranking badge
Updated Oct 22, 2026
H3 Fight Flow V1 | Continuous Fight Interaction LoRA on ModelTrends.ai: #425 Hottest AI model
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Also ranked: #60 Hottest MiniMax H3 model · #60 Hottest MiniMax H3 LoRA
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H3 Fight Flow V1 | Continuous Fight Interaction LoRA Popularity Trend
Heat score since 7 Oct 2026
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8,231°
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H3 Fight Flow V1 | Continuous Fight Interaction…: Heat score since 7 Oct 20267,000°7,345°7,689°8,034°8,379°8 Oct10 Oct13 Oct16 Oct19 Oct22 Oct8,231°ModelTrends.ai
7,000°
Floor
The scale runs from 0° to 9,999°. Everything below 7,000° is kept for models no source reports on yet, which carry a stand-in number there so lists stay complete. 7,000° is where measured data begins: a model with real data but almost no downloads sits at the floor, and the measurements fill the degrees above it. The floor says nothing about the model; only the degrees above it do, and they are what separates one model from another.
+861°
Civitai downloads
740 downloads of this exact version on Civitai. Downloads are the heaviest ingredient and are counted on a log scale: ten times the downloads adds the same 300°, so a model with a million downloads is not a thousand times hotter than one with a thousand. The six download sources share that one term, split between them in proportion to their counts.
+270°
Likes
62 likes and thumbs up across the sources. A like weighs half a download, on the same log scale.
+100°
Family boost
+100° because this is a LoRA of a family this site is nudging forward right now. It is a bounded nudge inside the score and is listed here openly; it can never hide a model or outweigh a thousandfold difference in downloads.
Show detailed breakdown
Every number on this site can be checked. This model's heat score is 8,231°, and here it is built one ingredient at a time, with the running total after each: the floor, the degrees each source adds, the bonus for the kind of model and what the age of its weights takes away. The colors are the bands of the chart above. The glossary at the end defines every term.
  1. 1
    Start at the floor.
    Why 7,000° and not zero: the scale runs from 0° to 9,999°, and the part below 7,000° is reserved for models no source reports on yet, which carry a stand-in number there so the lists stay complete and never outrank a model with data. 7,000° is where measured data begins. A model with real data but almost no downloads sits here; everything that follows is measurement, and the room above the floor holds ten tenfold steps in downloads at 300° each. The floor is the same for every model, so it decides nothing; the degrees above it do.
    7,000°
    running total
  2. 2
    Add the downloads.
    740 download-equivalents in all, from Civitai downloads. Ten times the downloads adds the same 300°, so size matters but never runs away with the score.
    +861°
    7,861°
    running total
  3. 3
    Add the likes.
    62 likes and thumbs up, at half the weight of a download.
    +270°
    8,131°
    running total
  4. 4
    Family boost.
    An open, bounded nudge for LoRAs of a family this site is pushing forward right now.
    +100°
    8,231°
    running total
  5. =
    The heat score.
    Where this model stands on every list of this site. Nothing else adjusts it.
    8,231°
Glossary: the terms used here
Heat score
One number for how much a model is used and wanted right now, from 0° to 9,999°. Every list on this site that says hottest is sorted by it and nothing else.
Floor
The 7,000° every model with real data starts from. The scale runs from 0° to 9,999°; the part below the floor is reserved for stand-ins (models without data), so that a model with data always ranks above one without. The floor is the same for everyone and decides nothing; the degrees above it are the measurement.
Download-equivalents
Everything the score treats as a download, added up: downloads themselves, each torrent seeder as 1,000, each AI Horde image and each run on a generation site as one.
Log scale
Counting by tens, not by ones: going from 1,000 to 10,000 downloads adds the same degrees as going from 10,000 to 100,000. It keeps giants from crowding out everything else.
Likes
Thumbs up and likes from every source, worth half a download each on the log scale.
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How many downloads a day a model gets right now, from the difference between two readings of a source. A quarter of the weight of the download term.
Measured and estimated
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Seeder
Someone who keeps a copy of the weights online for others to download over a torrent, or a hosted mirror doing the same. Each one counts as 1,000 downloads.
AI Horde
A volunteer network that generates images for free on donated computers. The number of images it has made with a model is public, and each counts as one download.
Generation sites
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How a model's growth over a period compares with the typical model's growth over the same period. Faster than typical reads as a rise, slower as a fall.
Typical model
The middle of the catalog: half the models with a figure grew faster over the period, half slower.
How this model's popularity has moved against the rest of the catalog: its growth in downloads, likes and usage over each period, measured against the typical model's growth over the same period, with its heat score at the time. Above the typical growth reads as a rise, below it as a fall. The past is reconstructed from today's totals, the model's first day and its measured download speed where two readings exist; a model that did not exist at the start of a period shows n/a.
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H3_Fight_Flow_V1.safetensors
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