| --- |
| license: creativeml-openrail-m |
| library_name: diffusers |
| pipeline_tag: text-to-image |
| --- |
| The model is created using the following steps: |
| - Find the desired model (checkpoint or lora) on Civitai |
| - You can see some conversion scripts in diffusesrs. This time, only the scripts for converting checkpoit and lora are used. |
| It depends on the model type of Civitai. If it is a lora model, you need to specify a basic model |
| - Using __load_lora function from https://towardsdatascience.com/improving-diffusers-package-for-high-quality-image-generation-a50fff04bdd4 |
| |
| |
| ``` |
| from diffusers import DiffusionPipeline |
| import torch |
| pipeline = DiffusionPipeline.from_pretrained( |
| "Andyrasika/lora_diffusion" |
| ,custom_pipeline = "lpw_stable_diffusion" |
| ,torch_dtype=torch.float16 |
| ) |
| lora = ("/content/lora_model.safetensors",0.8) |
| pipeline = __load_lora(pipeline=pipeline,lora_path=lora[0],lora_weight=lora[1]) |
| pipeline.to("cuda") |
| # pipeline.enable_xformers_memory_efficient_attention() |
| #https://huggingface.co/docs/diffusers/optimization/fp16 |
| pipeline.enable_vae_tiling() |
| prompt = """ |
| shukezouma,negative space,shuimobysim |
| a branch of flower, traditional chinese ink painting |
| """ |
| image = pipeline(prompt).images[0] |
| image |
| ``` |
| <hr> |
| |
| Since this is only the first official release, I believe there are still many, many imperfections. |
| Please provide feedback in time, and I will continuously make corrections, thank you! |
| |
| |
