|
--- |
|
license: creativeml-openrail-m |
|
library_name: diffusers |
|
tags: |
|
- stable-diffusion |
|
- stable-diffusion-diffusers |
|
- text-to-image |
|
- diffusers |
|
- diffusers-training |
|
- lora |
|
- stable-diffusion |
|
- stable-diffusion-diffusers |
|
- text-to-image |
|
- diffusers |
|
- diffusers-training |
|
- lora |
|
- stable-diffusion |
|
- stable-diffusion-diffusers |
|
- text-to-image |
|
- diffusers |
|
- diffusers-training |
|
- lora |
|
- stable-diffusion |
|
- stable-diffusion-diffusers |
|
- text-to-image |
|
- diffusers |
|
- diffusers-training |
|
- lora |
|
- stable-diffusion |
|
- stable-diffusion-diffusers |
|
- text-to-image |
|
- diffusers |
|
- diffusers-training |
|
- lora |
|
- stable-diffusion |
|
- stable-diffusion-diffusers |
|
- text-to-image |
|
- diffusers |
|
- diffusers-training |
|
- lora |
|
- stable-diffusion |
|
- stable-diffusion-diffusers |
|
- text-to-image |
|
- diffusers |
|
- diffusers-training |
|
- lora |
|
- stable-diffusion |
|
- stable-diffusion-diffusers |
|
- text-to-image |
|
- diffusers |
|
- diffusers-training |
|
- lora |
|
base_model: runwayml/stable-diffusion-v1-5 |
|
inference: true |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the training script had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
|
|
# LoRA text2image fine-tuning - iamkaikai/MATISSEE-LORA |
|
These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the iamkaikai/MATISSEE-ART dataset. You can find some example images in the following. |
|
|
|
![img_0](./image_0.jpg) |
|
![img_2](./image_2.jpg) |
|
![img_3](./image_3.jpg) |
|
![img_4](./image_0.png) |
|
![img_5](./image_13.png) |
|
![img_6](./image_17.png) |
|
|
|
|
|
|
|
## Intended uses & limitations |
|
|
|
#### How to use |
|
|
|
```python |
|
from diffusers import AutoPipelineForText2Image |
|
import torch |
|
|
|
pipeline = AutoPipelineForText2Image.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16, safety_checker=None).to("cuda") |
|
pipeline.load_lora_weights("iamkaikai/MATISSEE-LORA", weight_name="pytorch_lora_weights.safetensors") |
|
prompt = "MATISSEE-ART, brown, beige, coral, gray, orange red, violet, black, teal" |
|
for i in range(20): |
|
image = pipeline(prompt, num_inference_steps=20).images[0] |
|
image.save(f"./image_{str(i)}.png") |
|
``` |
|
|
|
#### Limitations and bias |
|
For some reason, this LORA model will often trigger the NSFW filter. Make sure you turn it off in the pipeline. |
|
|
|
## Training details |
|
|
|
[TODO: describe the data used to train the model] |