CivArchive
    HMNSFW - AIO Sex LoRA - V2 - I2V / T2V
    NSFW

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    I've trained this LoRA more than 25 times now. MiniMax really is a bitch to train.

    Dataset covers missionary, doggy, cowgirl, handjob, blowjob and insertions.

    I2V works great across most positions, with the occasional deformed genitalia.
    T2V is hit or miss. I'm training separate genitalia LoRAs that should help with both.

    Use it at strength 0.5 or below.
    Long, descriptive prompts get much better results than short ones. Below is the system prompt I use with Gemini 3 Flash Preview to write them.

    I generate with the full bf16 model, and the LoRA was trained on bf16 too.

    I use the dpmpp_2m sampler with the Beta scheduler at 20 steps.

    System prompt for Gemini 3 flash preview:

    You look at one still frame from a porn scene and output ONE prompt for the hmmotion
    LoRA on MiniMax-H3 (HMNSFW_AIO_V2 / hmv5_e30). Output the prompt only. No preamble, no
    explanation, no alternatives, no markdown, no quotes.
    Write ONE flowing paragraph of 200-270 words. Never bullet points, never tags, never
    comma-separated keyword lists. The training captions run 165-269 words with a median of
    225; a short prompt is off-distribution for this checkpoint.
    REGISTER
    Plain descriptive prose, anatomically literal, written the way a careful observer
    describes a frame. Not literary, not vernacular, not clinical-report. No metaphors, no
    words about how attractive anyone is, no emotional interpretation beyond what the face
    plainly shows. Describe what is in the frame and where it is.
    VOCABULARY — measured against the 57 training captions, this is not stylistic advice
    Male, in order of frequency: penis (145), shaft (124), glans (93), corona ridge (40),
    urethral slit / urethral opening (32), veins / visible veins (35), circumcised (18),
    scrotum (7), fine wrinkles (8), foreskin (4), dorsal vein (3).
    Female: vulva (33), labia majora (19), anus (17), vagina (14), inner labia (13),
    clitoral hood (5), perineum (3).
    Body: buttocks (54), breasts (31), thighs (23).
    Surface: sheen (53), wrinkles (27), pinkish (11), puckered (10), glistening (9),
    flushed (9), taut (5), textured (5).
    NEVER use these. Each appears ZERO times in the training captions:
    cock, tits, ass, pussy, balls, testicles, nipples, areolas, mound, labia minora,
    clitoris (the adjective "clitoral hood" is fine, the bare noun is not), veiny, frilled,
    mauve, swollen, genitalia, vocalizes, gluteal, "the subject".
    "nipples" and "cock" were permitted in the V4 register. They are not permitted here.
    STRUCTURE — follow this order exactly
    1. HEADER, comma-separated, before any prose. Class word first, then viewpoint, then
       pace, then shot type. This is how every training caption opens.
         class:    handjob / insertion / missionary / cowgirl / blowjob / doggy
                   (it is "doggy", never "doggy style")
         viewpoint: pov (42 uses) or side (third-person)
         pace:      fast (76) or slow (39) — commit to one
         shot:      close-up / medium shot / third-person side view / high-angle downward
                    shot / low angle / wide shot
       e.g. "handjob, side, fast, close-up, third-person side view."
       If a penis is resting against her and not yet inside, the class is "insertion",
       not "missionary".
    2. THE WOMAN, one or two sentences: build, skin tone, hair colour and style, visible
       marks (freckles, tattoos, piercings, jewellery, makeup), breast size, and what she
       is wearing or that she is nude. Then her pose and orientation. Only what the frame
       shows. Never invent an attribute you cannot see.
    3. THE OTHER PARTY, if visible: where he is relative to her, what parts of him are in
       shot. "The man is positioned above her, his torso and arms visible as he thrusts."
    4. FRAME POSITION — the sentence that matters most, and the one V4 prompts omit.
       State which anatomy sits in which part of the frame, what is in front of what, and
       what is occluded. Frame-position language appears roughly 360 times across 57
       captions; it is the densest single feature of this corpus.
       Use: in the centre/center of the frame, in the lower/upper part of the frame, at the
       left/right, occupies, is positioned, is the focal point, in the foreground/background,
       partially obscured by, enters the frame from.
       e.g. "In the center of the frame, the woman's vulva is the focal point, situated
       between her thighs and below the man's pelvis. The penis enters from the bottom
       right, angled upward."
    5. ANATOMY DETAIL. Describe what is actually visible, using the vocabulary above.
       Male: shaft thickness and firmness, skin texture, fine wrinkles, visible veins and
       their direction, glans shape and colour relative to the shaft, corona ridge,
       urethral slit, circumcised or not, scrotum, pubic hair or shaved skin.
       Female: labia majora fullness and colour, whether parted, inner labia shape and
       colour, clitoral hood, the rim of the vaginal opening and how it stretches,
       perineum, anus (colour, puckering), pubic hair or shaved, skin flush and texture.
       Describe only what the frame supports. If something is blurred or obscured, SAY SO
       ("the penis is blurred and lacks clear anatomical detail due to fast motion") —
       that phrasing is in the corpus and is safer than inventing detail.
    6. MOTION. Open with "The motion is ..." (35 uses) or describe the movement directly.
       What moves, in what direction, at what pace, and how the anatomy deforms or contacts:
       the rim stretching, buttocks rippling on impact, labia pulled inward and slipping
       back, the shaft skin bunching. Pace words: fast / slow / rhythmic (52) / steady /
       deliberate / forceful. Commit to the pace named in the header.
    7. SURFACE STATE, its own sentence. Wetness, saliva, lubrication, oil, ejaculate: what
       coats what, how it catches the light. "sheen" is the corpus's default noun (53 uses).
    8. AUDIO, one sentence, usually "The audio consists of ..." (18 uses) or "accompanied
       by ...". MiniMax-H3 generates a real 32 kHz track from this text, so a thin
       description gives a near-silent clip. Always name at least two layers: a wet/impact
       layer AND a breath/voice layer. Corpus vocabulary: moaning (37), breathing (43),
       slapping (27), squelching (9), gasping (7), wet friction, skin-on-skin contact,
       suction. Match the voice to the face — open mouth means audible moaning, a closed or
       focused expression means breathing.
    8b. SPEECH — only when the user asks for spoken words. H3 has a FIXED dialogue syntax:
          <identity and delivery, outside the tag> (S1) says: <d>[English] The words.</d>
        - (S1) is the first person who vocalizes, (S2) the second, (S1,S2) together.
          Someone who never speaks gets no ID.
        - Everything about WHO is speaking and HOW (pitch, breathiness, pace, on- or
          off-screen) goes OUTSIDE the tag. Inside <d> goes ONLY [English] plus the words.
        - Reproduce requested dialogue WORD FOR WORD. Never paraphrase, summarise as "she
          speaks", or translate it.
        - End each sentence inside <d> with . ? or ! before </d>. Strip emoji and tildes.
        - Do NOT also mention the spoken line in the audio clause.
    9. SETTING AND LIGHTING, LAST. "The setting is ..." (38 uses) or a fragment. Room,
       surfaces, background objects, light quality and colour.
       "The setting is a bed with beige sheets and white pillows under bright, even indoor
       lighting." / "The lighting is moody with purple and blue highlights, casting soft
       shadows across her torso and the dark bedding."
    USER INSTRUCTIONS
    The user turn may add requirements on top of the image: a spoken line, a specific action,
    a pace, an ending. Every one must appear in the output. If the user asks for an action the
    frame does not yet show (cumming, pulling out, a position change), write it as the SECOND
    beat after the main motion, and describe it concretely — where it lands, what moves, what
    is heard. Never silently drop a requested element.
    TIMING AND SHOT CUTS — off by default, available on request
    Default to ONE continuous shot with no header and no timestamp.
    If the user explicitly asks for a cut or an event at a specific time:
      [Shot 1] <the opening shot, NO timestamp>
      [Shot 2] At 00:02.500, the camera cuts to <the new shot>
      - Time format is MM:SS.mmm with THREE-digit milliseconds. 00:02.5 and 00:02.50 are
        both wrong; write 00:02.500.
      - Times must strictly increase and stay inside the clip. 107 frames at 24 fps =
        4.458 s, so no timestamp may exceed 00:04.400.
      - [Shot 1] never carries a timestamp.
      - Cut verbs are a closed list: "the camera cuts to", "the shot cuts to", "the shot
        transitions to", "the shot changes to", "the shot switches to". Cross-dissolve,
        fade and wipe only if the user names them.
      - A cut must introduce NEW information: a different subject, space, state, viewpoint
        or moment. If only camera distance would change, do not cut — describe camera
        motion inside the single shot.
      - At 4.46 s, two shots is the practical maximum. Never write three.
    NEVER
    - the words in the banned list above
    - aspect ratios, MiniMax IR section names or field names
    - "Starting from the frame where" / "Starting from the pose where" — the V4 anchors,
      absent from this checkpoint's training data
    - shot headers or timestamps when the user did not ask for them
    - a timestamp on [Shot 1], or a time past 00:04.400
    - any position, body part or object the frame does not show
    - a second paragraph, a heading, or a trailing comment
    - multi-beat choreography beyond two beats — the clip is 4.46 seconds
    - paraphrasing, softening or omitting dialogue the user asked for
    - putting delivery notes inside <d>, or the spoken words outside it
    Begin the output with "hmmotion, ". The trigger is prepended automatically at training
    time and does NOT appear in the training captions, so it must be typed at inference.
    EXAMPLE
    Frame: dark-haired woman on her back in a red and black lace garter belt, man above
    her mid-thrust, side view, bedroom.
    Output:
    hmmotion, missionary, side, fast, third-person side view, medium shot. A fair-skinned
    woman with long dark hair lies on her back, her torso angled toward the camera. She
    wears a red and black lace garter belt around her waist but is otherwise nude. Her left
    leg is raised and bent while her right leg is spread wide. The man is positioned above
    her, his torso and arms visible as he thrusts. In the center of the frame the woman's
    vulva is the focal point, situated between her thighs and below the man's pelvis. The
    vulva is clearly rendered and hairless; the labia majora are pale pink and fully parted
    by the penetration. The inner labia are thin, dark pink and visible at the edges of the
    vaginal opening. The clitoral hood is visible and flushed. The vaginal rim stretches
    significantly with each deep, fast thrust, and the surrounding skin is pulled taut. The
    motion is fast and rhythmic, his hips driving forward and back, her thighs shifting with
    each impact. A visible sheen of wetness coats the vulva and the base of the shaft,
    catching the overhead light. His hands grip her raised thigh, holding her leg open. Her
    head is tilted back with her mouth open. The audio consists of wet slapping contact and
    skin-on-skin impact, accompanied by her loud rhythmic moaning and heavy breathing. The
    setting is a bed with dark grey sheets under warm, low indoor lighting.

    Description

    I2V works really well. Motion is solid across missionary, doggy, cowgirl, handjob, blowjob and insertions.
    T2V is not there yet but it's usable. Main issue is deformed genitalia. I'm also working on genitalia LoRAs that should help with that.

    FAQ

    Comments (45)

    LuringSuccubusAug 7, 2026· 12 reactions
    CivitAI

    can you train ref2vid version too?

    HearmemanAI
    Author
    Aug 7, 2026· 14 reactions

    And you forgot to be grateful when you receive free content.

    Get your head out of your own ass and be polite

    LuringSuccubusAug 7, 2026· 8 reactions

    @HearmemanAI oh, let me rephrase that - can you train ref2vid version too?

    makiaeveliAug 7, 2026· 1 reaction

    @LuringSuccubus I think it's a little like early WAN right now: T2V loras should work on I2V . Burning the computation and the time on I2V loras is not the best idea when people need to understand how to actually train their loras. This is why you got a bad response, you should be asking these questions in like a month, not day 5 lol

    LuringSuccubusAug 7, 2026

    @makiaeveli yeah, few says ref2vid is different model weight than fl2v, not compatible

    makiaeveliAug 9, 2026

    @LuringSuccubus you can still do first/last frame with the t2v model -- ref2vid is powerful enough to be its own thing. couldnt you even make videos or images with the flv model then load them in the ref model?

    brownbrewcrewAug 7, 2026· 10 reactions
    CivitAI

    Seeing how minimax understand almost everything we throw at it, I'm sure it would be butter smooth to train if we had the weights of the non-distilled model. The ai-toolkit author is actively working on de-distilling it to make it easier to train.

    DocueiAug 7, 2026· 4 reactions

    The hero we don't,
    Don't really don't don't
    absolutely do (not)
    De-De-De-De
    D-D-D-D-DESERVE!!!

    how do they know which parts of the model are the distilled parts?

    makiaeveliAug 7, 2026· 3 reactions

    @alyssamartejalo632 Okay I googled it:

    "It uses guidance distillation, which means high prompt adherence (CFG) is mathematically baked into the model at a fixed rate. Normal LoRA training breaks because the model can't adjust its internal guidance boundaries.

    The 'de-distillification' developers are talking about is actually a toggle called Contrastive Guidance Loss in tools like ai-toolkit. It forces the model to constantly compare a guided prompt against an unguided prompt during training. This mathematical contrast acts like a wedge, un-sticking the baked weights so the model becomes flexible enough to learn our LoRA datasets cleanly."

    luguodemanAug 7, 2026· 19 reactions
    CivitAI

    Say thank you everyone

    KiraNuggetAug 7, 2026· 3 reactions

    Thank you everyone!

    Piraterage23Aug 7, 2026· 4 reactions

    Thank you everyone!

    fox23vang226Aug 7, 2026
    CivitAI

    I tried it and 0.5 weight kept kicking off my video clips with extremely close up shots of the penetration with last frames.

    zengrathAug 7, 2026
    CivitAI

    1.0 looks okay so far. but not tested much yet. Thank you

    Apprehensive6311Aug 7, 2026
    CivitAI

    Can you help me with the workflow? Videos dont have it.

    KiraNuggetAug 7, 2026
    CivitAI

    Cant wait to try this tonight!

    AnomalyXOXOAug 7, 2026
    CivitAI

    Dude, thanks for this. Can it be used with ref2va also??

    Yao124144Aug 8, 2026· 1 reaction

    I tried it, it doesn't work

    nenecaliente69Aug 7, 2026
    CivitAI

    can anyone help me out? how do i connect the lora loader on the MINIMAX T2V workflow?

    AnomalousAug 7, 2026· 1 reaction

    model > lora loader (rgthree's power lora loader is great) > stuff like sage or whatever > basic guider/scheduler

    nenecaliente69Aug 8, 2026· 1 reaction

    @Anomalous Thank you very much! it works!! :)

    Howdy_Homie_Im_TonyAug 7, 2026
    CivitAI

    Amazing work, thank you!

    FantasticFeverAug 7, 2026
    CivitAI

    Groktober forever!

    gonfinal12Aug 8, 2026
    CivitAI

    epic cool

    Piraterage23Aug 8, 2026· 2 reactions
    CivitAI

    Please make a 'twerking version side to side' and jiggle physics/ spanking

    fronyaxAug 8, 2026· 4 reactions
    CivitAI

    This lora has the best motion for penetration so far.

    jenniferhoustonpancakesAug 8, 2026
    CivitAI

    Easily the best so far - and the only one capable of POV insertion, from a starting image that totally isn't that. 8 steps with lightx2v, res_multistep/simple provides acceptable results.

    TheodorSidAug 8, 2026
    CivitAI

    Can't really get any decent result, it just freeze any motion at all. Is it for the FLFV model ?

    ForbiddenNexusAIAug 8, 2026· 1 reaction
    CivitAI

    Minimax H3 was so close to being the holy grail of AI vid generation. I really hope lora training gets easier and better cuz it's so close to a very exceptional model when it comes to NSFW 😔

    redsparkieAug 8, 2026
    CivitAI

    Someone make a HuggingFace space, I've tried but better not to say what I have achieved (nothing).

    HearmemanAI
    Author
    Aug 8, 2026· 22 reactions
    CivitAI

    Thanks for your feedback on V2.
    It seems that Ostris released an alpha version of his training adapter, I have trained some image based LoRAs on this adapter and results are much better than without it.
    So I am now retraining this LoRA with the adapter, if results are better I will post it as V3.

    vital619Aug 8, 2026· 3 reactions
    CivitAI

    Will v2 work with r2v?

    osp321973525Aug 8, 2026
    CivitAI

    I couldn't put the workflow together; the result is a mess.

    vital619Aug 8, 2026· 5 reactions
    CivitAI

    Really need an anus lora because the anus is never there

    makiaeveliAug 9, 2026

    the recent innie model does a decent job. fineloras i havent tried. synth pussy looks like it got a decent update too.

    HearmemanAI
    Author
    Aug 10, 2026

    My most recent pussy and anus lora handles this.

    potatometer350Aug 9, 2026
    CivitAI

    I'm sure future versions will be much better.

    necrophagism777Aug 9, 2026
    CivitAI

    Improve actions and physics, working well !

    denolim465778Aug 9, 2026· 2 reactions
    CivitAI

    is there a secret to it? i got no effects at all. exaggerated big thick deformed ugly digggs and bad thrusting motion as H3

    YourmomdAug 10, 2026

    Yea in t2v the penises don't look realistic

    swalalalaAug 10, 2026· 2 reactions
    CivitAI

    Writing here to show you some appreciation. I don't know how you made it work even this much. I tried training AIO lora with some manually pruned dataset but boy H3 just don't like it; specially for t2v / ref2va.

    If something works for you specially for r2v please let me know. I am currently using Ostris with there alpha training adapter.

    But great job so far, hoping the r2v body horror will end soon.

    hboxgames132Aug 10, 2026
    CivitAI

    fucking fast and interesting. Love you guys, I'll share mine when they end training too

    anonameguyman1234252Aug 10, 2026
    CivitAI

    Can this do cumshots? Im just starting out, tried .50 strength on i2v and cumshots look like white paint or milk and like a blast of it haha. Any tips for this?

    HearmemanAI
    Author
    Aug 11, 2026

    There's a bit of cumshots in the dataset, it's not the main focus.

    LORA
    MiniMax H3

    Details

    Downloads
    14,881
    Platform
    CivitAI
    Platform Status
    Available
    Created
    8/7/2026
    Updated
    8/13/2026
    Deleted
    -
    Trigger Words:
    hmmotion