Model Detail
face-swap
—face-swap is an image generation model with 9B parameters released by ilkerzgi. The model is registered under the image-to-image pipeline tag on Hugging Face, distributed under a other license.
face-swap ships with 9B parameters. Distribution is governed by the other license — review the exact terms before commercial deployment.
face-swap is best fit for text-to-image generation and creative iteration. It is a less obvious choice for production photography pipelines that need exact reproducibility. Treat this as a starting matrix rather than a benchmark verdict — the right deployment usually depends on the specific evaluation suite that mirrors your workload.
Does an Illumination Prior Help Face-Swap Detection? A Controlled Study of Temporal Self-Blended Images
arXiv:2610.11706v1 Announce Type: new Abstract: Self-blended images are widely used to train face-swap detectors, but primarily capture blending artifacts. We investigate whether adding illumination inconsistencies improves detection. Temporal Self-Blended Images (T-SBI) transfer lighting statistics
Camera-Noise Residuals for Face-Swap Detection: Redundant, Not Complementary, and Why
arXiv:2610.11683v1 Announce Type: new Abstract: Fusing a learned camera-noise fingerprint with an RGB appearance backbone is an appealing route to generator-independent deepfake detection, because the noise residual is grounded in image-formation physics rather than in the texture statistics of a pa
Hugging Face CEO warns that Netflix’s OpenAI hack documentary isn’t accurate
Before you share the Netflix documentary "AI Gone Rogue," take note. Clem Delangue, Hugging Face's co-founder who is featured in the film, says it went "full doomer mode" and isn't accurate.
Hugging Face ❤️ TorchTPU: TPUs, Natively
Embedded AI evaluators won’t be an easy solution, Hugging Face’s policy chief says
The idea of embedded evaluators — in which supposedly "neutral" third-party observers are placed inside AI organizations — has been popularized over the last several months, as AI labs grapple with a rash of safety incidents that have spurred concerns over the potential harms of their technology.
Happy Young Women, Grumpy Old Men? Emotion-Driven Demographic Biases in Synthetic Face Generation
arXiv:2602.00032v4 Announce Type: replace-cross Abstract: Synthetic faces from text-to-image (T2I) models pervade digital media, yet their demographic biases under emotionally conditioned prompts remain poorly understood. We aim to systematically audit how emotionally conditioned prompts affect demo
