Type | |
Stats | 486 501 |
Reviews | (42) |
Published | Jul 30, 2024 |
Base Model | |
Training | Steps: 9,758 Epochs: 17 |
Usage Tips | Clip Skip: 1 |
Hash | AutoV2 6DB9D6F075 |
🎭 Emotion Puppeteer - SDXL LoRA 🎭
Use this model to win a 20K buzz bounty! (Ends August 31, 2024)
How to use
Use this visual cheats sheet showing possible 96 eye-mouth combinations
👁️ grieving, glaring, gazing, seething, beaming, eyes wide, winking, squinting
👄 frowning, pouting, smiling, laughing, singing, screaming, sneering, snarling, grimacing, breathing, gasping, puckering, resting, relaxing
Add one more 👁️ words and/or 👄 mouth words to your prompt
For a stronger effect, increase the weight of the 👁️ / 👄 words, and/or increase the lora weight up to 1.2
Suggestions
Feedback and questions welcome. Please share your results!
Best for closeups. Most training images head and shoulders or closer
Best with square aspect ratio. All training images were square
Best for realism. Most training images were photos
For character consistency, use a combination of controlnets
Keep your negative prompt short
Other optional prompts
These words were all used in training, but their effect is weaker:
gnashing, cackling, flirting, glowering, leering, kissing, shrieking, shouting, smooching, sniffling, threatening, tisking, taunting, vomiting, wincing, yelling, accusatory, agony, amused, angry, anguish, annoyed, appalled, approving, aroused, ashamed, astonished, awestruck, bemused, bewildered, bitter, blame, certain, cheerful, cocky, concentrating, concerned, confident, confusion, contempt, contemptuous, content, crazed, crestfallen, crushed, curious, dazed, defiant, delighted, depressed, despairing, determined, disappointed, disapproving, disbelief, disgusted, dismayed, distrust, disturbed, dominant, ecstatic, embarrassed, enraged, envious, euphoric, evil grin, exasperated, excited, flirtatious, frightened, frustrated, furious, gentle, gleeful, happily, happy, hate, heartache, heartbroken, helpless, horrified, hurt, hurting, impatient, impressed, in love, incredulous, insane, insolent, intrigued, jubilant, judgemental, loathing, lustful, merry, misery, mistrust, mocking, nauseated, nonplussed, outraged, overjoyed, passionate, perplexed, petulant, pissed off, pitying, playful, puzzled, regretful, repulsed, revolted, rude, sad, scared, scorn, seductive, seizure, shaken, shocked, sickened, silenced, skeptical, smarmy, sour, startled, stunned, submissive, sultry, surprised, suspicious, terrified, thinking, ticked off, uncertain, unconvinced, unsettled, vexed, violent, wonder
How it was trained
I used ~300 high-resolution images, mostly photos, curated and captioned by hand. Sorry, I can't share the training images due to the need to protect the privacy of the subjects.
Each training image's captions included one word for the mouth type and one for the eye type. Some combinations had much higher representation in the data that others. All captions also included 2 to 4 specific matching emotions. The captions didn't include any other words. No other descriptions of the subject, physical parts of the face, background, style, or quality. Caption shuffling was used. Prior preservation wasn't. ~10K steps with default LR.