Downloads · 30 days
21
5% of all-time downloads
kmilesz/affinis
affinis is a text-to-image model from kmilesz. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as openrail++.
Downloads · 30 days
21
5% of all-time downloads
All-time downloads
408
Public
Repo size
193 MB
Likes
1
Public
Click a slice to open those files.
.safetensors186 MB · 95%
From the Hugging Face model README
affinis.safetensors here 💾.
models/Lora folder.<lora:affinis:1> to your prompt. On ComfyUI just load it as a regular LoRA.affinis_emb.safetensors here 💾.
embeddings folderaffinis_emb to your prompt. For example, A photo of affinis_emb
(you need both the LoRA and the embeddings as they were trained together for this LoRA)from diffusers import AutoPipelineForText2Image
import torch
from huggingface_hub import hf_hub_download
from safetensors.torch import load_file
pipeline = AutoPipelineForText2Image.from_pretrained('stabilityai/stable-diffusion-xl-base-1.0', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('kmilesz/affinis', weight_name='pytorch_lora_weights.safetensors')
embedding_path = hf_hub_download(repo_id='kmilesz/affinis', filename='affinis_emb.safetensors' repo_type="model")
state_dict = load_file(embedding_path)
pipeline.load_textual_inversion(state_dict["clip_l"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder, tokenizer=pipeline.tokenizer)
pipeline.load_textual_inversion(state_dict["clip_g"], token=["<s0>", "<s1>"], text_encoder=pipeline.text_encoder_2, tokenizer=pipeline.tokenizer_2)
image = pipeline('A photo of <s0><s1>').images[0]
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: madebyollin/sdxl-vae-fp16-fix.