---
base_model: stable-diffusion-v1-5/stable-diffusion-v1-5
library_name: diffusers
license: creativeml-openrail-m
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
inference: true
datasets:
- logo-wizard/modern-logo-dataset
---

<!-- This model card has been generated automatically according to the information the training script had access to. You
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# LoRA text2image fine-tuning - SedatAl/test-test
These are LoRA adaption weights for stable-diffusion-v1-5/stable-diffusion-v1-5. The weights were fine-tuned on the logo-wizard/modern-logo-dataset dataset.


![img_1](./7c970728-3193-4d89-8461-514bae4007af.jpeg)
![img_2](./image_2.png)
![img_3](./image_3.png)



## How to Use

```python
from diffusers import DiffusionPipeline

pipe = DiffusionPipeline.from_pretrained("stable-diffusion-v1-5/stable-diffusion-v1-5")
pipe.load_lora_weights("SedatAl/test-test")

prompt = "a logo of electronic online shop, gradient image of a rectangular shopping bag with a cursor inside, white background, red and magenta gradient foreground, minimalism, modern"
image = pipe(prompt).images[0]

```

## Training details

  --train_batch_size=10 \
  --max_train_steps=200 \
  --learning_rate=1e-04 \

 Remaining parameters are default.