Optimize Flux LoRA Headshot Trainer from Replicate
Budget: €8 – €30 EUR
I’ve built a headshot-generation pipeline that uses the Flux LoRA Trainer inside a React + Supabase application. The current results look passable, but they still miss the mark on realism—especially in the finer facial details that sell a photo as authentic. I’m looking for someone who can drill into the LoRA hyper-parameters, loss settings, and training schedule so the model produces far more faithful, lifelike portraits.
My top priority is facial detail. In practice that means the output must consistently get these three areas right:
• Eyes and eyebrows
• Mouth and smile
• Skin texture
You’ll receive access to the existing repo, sample datasets, and the Supabase storage bucket where we log checkpoints. The job is to experiment, document, and commit an updated configuration (or code tweaks) that measurably improves those focus areas. I don’t mind if training runs take a little longer, as long as the visual fidelity jumps noticeably.
Deliverables
• A tuned set of Flux LoRA Trainer parameters committed to the repo, clearly commented.
• Before / after comparison images and a short note explaining what changed and why it works.
• A concise “how to reproduce” section in the README so I can retrain or fine-tune further without guesswork.
I’ll test the new setup by running the same prompt set on my side and doing an A/B comparison. If the updated model reliably captures sharper eyes, natural smiles, and convincing skin texture, we’re good.
My top priority is facial detail. In practice that means the output must consistently get these three areas right:
• Eyes and eyebrows
• Mouth and smile
• Skin texture
You’ll receive access to the existing repo, sample datasets, and the Supabase storage bucket where we log checkpoints. The job is to experiment, document, and commit an updated configuration (or code tweaks) that measurably improves those focus areas. I don’t mind if training runs take a little longer, as long as the visual fidelity jumps noticeably.
Deliverables
• A tuned set of Flux LoRA Trainer parameters committed to the repo, clearly commented.
• Before / after comparison images and a short note explaining what changed and why it works.
• A concise “how to reproduce” section in the README so I can retrain or fine-tune further without guesswork.
I’ll test the new setup by running the same prompt set on my side and doing an A/B comparison. If the updated model reliably captures sharper eyes, natural smiles, and convincing skin texture, we’re good.