---
tags:
- stable-diffusion-xl
- stable-diffusion-xl-diffusers
- text-to-image
- diffusers
- lora
- template:sd-lora
widget:
- text: A <s0><s1> character, An underwater humanoid that floats surrounded by coral,
    fish and algae, with translucent skin, no genus, no nose, a soft body, large fish-like
    antennae on the face, and tentacular, webbed extremities. In the background, a
    submarine cave lets in light from the surface. Photorealistic
  output:
    url: image-0.png
- text: A <s0><s1> character, An underwater humanoid with salt crystals on its face
    floating in a seated position surrounded by fish, coral and algae, with translucent
    skin, no genus, no nose, veins and organs visible through the skin, spaced-aperture
    eyes without a globe, and webbed extremities. In the background, a submarine cave
    lets in light from the surface. Photorealistic
  output:
    url: image-1.png
- text: A <s0><s1> character, An underwater humanoid-algae that swims surrounded by
    coral and fish and algae, harvests algae, with translucent skin, no genus, no
    nose, organs visible through the skin, it has a head of large fish antennae on
    its face, and tentacular, webbed extremities. Fish are attached to its body. In
    the background, a submarine cave lets in light from the surface. Photorealistic
  output:
    url: image-2.png
- text: A <s0><s1> character, A winged underwater humanoid sits surrounded by its
    garden of coral and algae, with translucent, genderless skin, a snout-like nose,
    muscles and organs visible through the skin, large globe-shaped eyes and webbed
    extremities. In the background, a submarine cave lets in light from the surface.
    Photorealistic
  output:
    url: image-3.png
- text: A <s0><s1> character, An underwater humanoid crowned with translucent antennae
    appears from behind corals and algae, with translucent skin, no genus, no nose,
    muscles and organs visible through the skin, flexible, tubular limbs, no eyes,
    and slender, humanoid extremities.  In the background, a submarine cave lets in
    light from the surface. Photorealistic
  output:
    url: image-4.png
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: A <s0><s1> character
license: openrail++
---

# SDXL LoRA DreamBooth - computational-mama/underwater-humanoid

<Gallery />

## Model description

### These are computational-mama/underwater-humanoid LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0.

## Download model

### Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke

- **LoRA**: download **[`underwater-humanoid.safetensors` here 💾](/computational-mama/underwater-humanoid/blob/main/underwater-humanoid.safetensors)**.
    - Place it on your `models/Lora` folder.
    - On AUTOMATIC1111, load the LoRA by adding `<lora:underwater-humanoid:1>` to your prompt. On ComfyUI just [load it as a regular LoRA](https://comfyanonymous.github.io/ComfyUI_examples/lora/).
- *Embeddings*: download **[`underwater-humanoid_emb.safetensors` here 💾](/computational-mama/underwater-humanoid/blob/main/underwater-humanoid_emb.safetensors)**.
    - Place it on it on your `embeddings` folder
    - Use it by adding `underwater-humanoid_emb` to your prompt. For example, `A underwater-humanoid_emb character`
    (you need both the LoRA and the embeddings as they were trained together for this LoRA)
    

## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)

```py
from diffusers import AutoPipelineForText2Image
import torch
from huggingface_hub import hf_hub_download
from safetensors.torch import load_file
        
pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('computational-mama/underwater-humanoid', weight_name='pytorch_lora_weights.safetensors')
embedding_path = hf_hub_download(repo_id='computational-mama/underwater-humanoid', filename='underwater-humanoid_emb.safetensors' repo_type="model")
state_dict = load_file(embedding_path)
pipeline.load_textual_inversion(state_dict["clip_l"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
pipeline.load_textual_inversion(state_dict["clip_g"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2)
        
image = pipeline('A <s0><s1> character').images[0]
```

For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)

## Trigger words

To trigger image generation of trained concept(or concepts) replace each concept identifier in you prompt with the new inserted tokens:

to trigger concept `TOK` → use `<s0><s1>` in your prompt 



## Details
All [Files & versions](/computational-mama/underwater-humanoid/tree/main).

The weights were trained using [🧨 diffusers Advanced Dreambooth Training Script](https://github.com/huggingface/diffusers/blob/main/examples/advanced_diffusion_training/train_dreambooth_lora_sdxl_advanced.py).

LoRA for the text encoder was enabled. False.

Pivotal tuning was enabled: True.

Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.