cookey39/blue_reflection
Viewer • Updated • 20 • 35
How to use cookey39/reflector with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("cookey39/reflector", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]https://www.pixiv.net/artworks/119270564
https://www.pixiv.net/artworks/119269797
reflector.safetensors here 💾.models/Lora folder.<lora:reflector:1> to your prompt. On ComfyUI just load it as a regular LoRA.reflector_emb.safetensors here 💾.embeddings folderreflector_emb to your prompt. For example, blue_reflection:
(you need both the LoRA and the embeddings as they were trained together for this LoRA)from diffusers import AutoPipelineForText2Image
from diffusers import DiffusionPipeline, DDIMScheduler
import torch
from huggingface_hub import hf_hub_download
from safetensors.torch import load_file
pipeline = AutoPipelineForText2Image.from_pretrained('cookey39/reflector', torch_dtype=torch.float16).to('cuda')
# lower eta results in more detail
instance_token = "<s0><s1>"
prompt = f"a {instance_token}masterpiece, best quality,long hair, cute face, white kneehighs, black hair, hair strand, twin braids, cat hair ornament, adorable girl, absurdres, huge_filesize, Japanese, game_cg, {instance_token} "
negative_prompt = "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, bad feet, "
image = pipeline(prompt=prompt, negative_prompt = negative_prompt, num_inference_steps=50, cross_attention_kwargs={"scale": 1.0},width = 720, height=1080).images[0]
image
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
To trigger image generation of trained concept(or concepts) replace each concept identifier in you prompt with the new inserted tokens:
to trigger concept TOK → use <s0><s1> in your prompt
All Files & versions.
The weights were trained using 🧨 diffusers Advanced Dreambooth Training Script.
LoRA for the text encoder was enabled. False.
Pivotal tuning was enabled: True.
Special VAE used for training: None.