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A SigLIP 2 ViT (image encoder only) for timm. Equivalent to image tower from
fluorite (arknights)
Works best at 0.75 weight.
This is an embedding of a woman that I've generated consistent faces of thru SD and decided to make into an embedding for easier access in the future. It uses a mere 5 tokens.
Works best between 0.8 & 1.0
A RoPE ViT image classification model. The model follows a two-stage training process: first, CAPI pretraining, then fine-tuned on the ImageNet-21K dataset.
Loving this model? Get the Pro version of my models here for exclusive perks and early access to unique resources.
GGUF quantizations of empero-ai/Qwythos-9B-Claude-Mythos-5-1M for llama.cpp, Ollama, LM Studio, jan, KoboldCpp, and other GGUF runtimes.
