| | --- |
| | tags: |
| | - autotrain |
| | - stable-diffusion |
| | - stable-diffusion-diffusers |
| | - text-to-image |
| | - diffusers |
| | - lora |
| | - template:sd-lora |
| |
|
| | base_model: Lykon/DreamShaper |
| | instance_prompt: photo of Ronaldo men |
| | license: openrail++ |
| | --- |
| | # ModelsLab LoRA DreamBooth Training - stablediffusionapi/my-stablediffusion-lora-3370 |
| | These are LoRA adaption weights for Lykon/DreamShaper. The weights were trained on photo of Ronaldo men using [ModelsLab](https://modelslab.com). |
| | LoRA for the text encoder was enabled: False. |
| |
|
| | ## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers) |
| | ```py |
| | !pip install -q transformers accelerate peft diffusers |
| | from diffusers import DiffusionPipeline |
| | import torch |
| | |
| | pipe_id = "Lykon/DreamShaper" |
| | pipe = DiffusionPipeline.from_pretrained(pipe_id, torch_dtype=torch.float16).to("cuda") |
| | pipe.load_lora_weights("stablediffusionapi/my-stablediffusion-lora-3370", weight_name="pytorch_lora_weights.safetensors", adapter_name="abc") |
| | prompt = "abc of a hacker with a hoodie" |
| | lora_scale = 0.9 |
| | image = pipe( |
| | prompt, |
| | num_inference_steps=30, |
| | cross_attention_kwargs={"scale": 0.9}, |
| | generator=torch.manual_seed(0) |
| | ).images[0] |
| | image |
| | ``` |
