






I gathered 34 images of Salma Hayek. Majority of photos were from red carpet events and less from movies. Some of the images were full body as I wanted to retain her face even when zoomed out. I used Blip captioning to generate the filewords and edited each individually to reduce potential hallucinations. I added a 1 to the end of Hayek on the embedding name to ensure there is no mixing with previously trained images of her.
I used 0.005:100:0,0.0025:250,0.001:500,0.0005:1000,0.00025 for my learning rate. I am going for 2.5K training steps total. I am using a batch size of 1 with Gradient Accumulation Steps set to 3. I am running on a RTX 4090 on the cloud. I am using 12.5 out of 24 GB. The estimated time of completion is .5 hours. For the embedding I am using 8 vectors per token. I switched to SD 1.5 EMA Only model for training.
1. The rights to reposted models belong to original creators.
2. Original creators should contact SeaArt.AI staff through official channels to claim their models. We are committed to protecting every creator's rights. Click to Claim
