sdxl-mk1 / README.md
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---
license: creativeml-openrail-m
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt: <s0><s1>
inference: false
---
# sdxl-mk1 LoRA by [asronline](https://replicate.com/asronline)
### Generate Mortal Kombat 1 fighters and character skins
![lora_image](https://tjzk.replicate.delivery/models_models_cover_image/f3a6ec2c-1147-42fb-ab0f-2208c0a42d95/out-0-49.png)
>
## Inference with Replicate API
Grab your replicate token [here](https://replicate.com/account)
```bash
pip install replicate
export REPLICATE_API_TOKEN=r8_*************************************
```
```py
import replicate
output = replicate.run(
"sdxl-mk1@sha256:7ad4307597a51cbe61a568e835f8f475d33b97b0987117c5a89cbf0e699eb69c",
input={"prompt": "In the style of MK1, scorpion in the style of a dark and mysterious ninja costume, black and misty details, fiery eyes and hands, skull as his head"}
)
print(output)
```
You may also do inference via the API with Node.js or curl, and locally with COG and Docker, [check out the Replicate API page for this model](https://replicate.com/asronline/sdxl-mk1/api)
## Inference with 🧨 diffusers
Replicate SDXL LoRAs are trained with Pivotal Tuning, which combines training a concept via Dreambooth LoRA with training a new token with Textual Inversion.
As `diffusers` doesn't yet support textual inversion for SDXL, we will use cog-sdxl `TokenEmbeddingsHandler` class.
The trigger tokens for your prompt will be `<s0><s1>`
```shell
pip install diffusers transformers accelerate safetensors huggingface_hub
git clone https://github.com/replicate/cog-sdxl cog_sdxl
```
```py
import torch
from huggingface_hub import hf_hub_download
from diffusers import DiffusionPipeline
from cog_sdxl.dataset_and_utils import TokenEmbeddingsHandler
from diffusers.models import AutoencoderKL
pipe = DiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-xl-base-1.0",
torch_dtype=torch.float16,
variant="fp16",
).to("cuda")
load_lora_weights("areshi/sdxl-mk1", weight_name="lora.safetensors")
text_encoders = [pipe.text_encoder, pipe.text_encoder_2]
tokenizers = [pipe.tokenizer, pipe.tokenizer_2]
embedding_path = hf_hub_download(repo_id="areshi/sdxl-mk1", filename="embeddings.pti", repo_type="model")
embhandler = TokenEmbeddingsHandler(text_encoders, tokenizers)
embhandler.load_embeddings(embedding_path)
prompt="In the style of MK1, scorpion in the style of a dark and mysterious ninja costume, black and misty details, fiery eyes and hands, skull as his head"
images = pipe(
prompt,
cross_attention_kwargs={"scale": 0.8},
).images
#your output image
images[0]
```