MiniMax-H3-Realism-People-LoRA

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What MiniMax-H3-Realism-People-LoRA is

MiniMax H3 Realism People LoRA Trigger word: r34l1sm A LoRA adapter for MiniMax H3 specialized in realistic people: faces that hold up in close-up, natural skin texture, believable expressions and gestures, film-style lighting and documentary camera movement. Same prompt, same seed — base model on the left, this adapter on the right: Before / after 19 pairs, same prompt, same seed, adapter on vs off — the only variable is the LoRA. The trigger word is present on both sides, so it is not doing the work. Each pair plays the base model first, then freezes and dims while the adapted version plays beside it. Close-up talking faces, arguments, several people speaking at once, weathered skin, children, ritual and travel scenes. Nothing cherry-picked from a larger render batch: these are the pairs that were kept, in order. (download the comparison, 197s, 1920x1080) What it does MiniMax H3 is already a strong general video model. This adapter pushes it further on human-centered shots: portraits, faces, hands at work, crowds and everyday characters. Skin keeps its texture instead of smoothing out, eyes and micro-expressions stay coherent, light behaves like it does on a film set, and motion gains a subtle handheld quality. It keeps H3's native synchronized audio. It is the successor of MiniMax-H3-Realism-LoRA, retrained on a larger dataset focused on people. How to use These are plain LoRA weights. Nothing here is tied to a hosted service — run them wherever you run MiniMax H3. Locally, in ComfyUI Download the .safetensors and drop it in models/loras/, then insert a Load LoRA node between your model loader and the sampler. No conversion step: the keys are the standard H3 layout (diffusionmodel.blocks.N.attn.qkvproj, fused QKV), the same one other working H3 LoRAs use, so ComfyUI loads it as-is. Start the prompt with the trigger word r34l1sm, then describe the scene. Scale 1.0 is the intended strength; 0.6-0.8 for a lighter touch. It works on text to video, image to video and reference to video, since the adapter only touches the shared attention projections. In your own code Any inference stack that can apply a LoRA to H3 will take it. The application is the usual Weff =

Summarised from the published model card. Read the full card on the HuggingFace links below.

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What it is

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Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys minimax-h3-realism-people-lora for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (minimax-h3-realism-people-lora below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/videos/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"minimax-h3-realism-people-lora","prompt":"a drone shot over a forest"}'

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