Suraj Patil
Core ML Engineer, Hugging Face | Diffusers Core Maintainer | Generative Vision Specialist
Verified Proof of Work Artifacts
2 items catalogedEach artifact below represents an authenticated research publication, production code repository, or technical architectural framework directly authored or co-created by Suraj Patil. Every entry undergoes editorial source verification.
Fine-Tuning Stable Diffusion with LoRA and ControlNet
Authored the definitive implementation and engineering guide for Low-Rank Adaptation (LoRA) applied to cross-attention layers of text-to-image latent diffusion models, slashing VRAM training requirements from 80GB to under 8GB.
Low-rank approximations can degrade fine textural fidelity when fine-tuning across drastically different visual domains.
Diffusers: State-of-the-Art Diffusion Models in PyTorch
Engineered core schedulers (DDIM, DPMSolver, Euler), memory-efficient cross-attention kernels, and quantized pipeline architectures powering Stable Diffusion and Flux ecosystem inference.
Diffusion sampling requires multiple sequential denoising steps, bottlenecking latency relative to single-pass adversarial models.