NSFW Content Filter

User Guide (Latest Version)

NSFW Content filtering model offers vision based filtering solution to find explicit content. Its main use case is to check outputs of the generative models like Stable Diffusion. Model combines zero-shot capabilities of pretrained CLIP with a linear probing approach for fine tuning.

During fine-tuning, a light classification layer is trained on top of the frozen CLIP encoder, significantly improving the quality of detecting NSFW Content compared to just zero-shot classification.

Feature

Training

Inference

Data parallelism Yes N/A
Tensor parallelism N/A N/A
Pipeline parallelism N/A N/A
Sequence parallelism N/A N/A
Activation checkpointing Yes (Uniform or Block) No
FP32/TF32 Yes Yes (FP16 enabled by default)
AMP/FP16 Yes Yes
AMP/BF16 Yes Yes
BF16 O2 Yes No
TransformerEngine/FP8 No No
Multi-GPU Yes Yes
Multi-Node Yes Yes
Inference deployment N/A NVIDIA Triton supported
SW stack support Slurm DeepOps/Base Command Manager/Base Command Platform Slurm DeepOps/Base Command Manager/Base Command Platform
NVfuser No N/A
Distributed Optimizer N/A N/A
TorchInductor No N/A
Flash Attention No N/A
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© | | | | | | |. Last updated on Jun 14, 2024.