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Semantic segmentation model fine-tuned from nvidia/mit-b5 with CelebAMask-HQ for face parsing. For additional options, see the Transformers Segformer docs.
Works best at 0.75 weight.
This model is a fine-tuned version of dandelin/vilt-b32-mlm on the vqa dataset.
Should create Latte Art, but not sure if working, have to figure it out! 😆
This model has been pushed to the Hub using the PytorchModelHubMixin integration: Library: [More Information Needed] Docs: [More Information Needed]
timm compatible AIM-v2 ( image encoder weights from
Bubbles, nice lass that she is, despite her parents being idiots since they named her "Bubbles", is fortunately completely imaginary and has therefore never been bullied with her name.
timm PaliGemma2 (SigLIP image encoder only, with global avg pooling) weights from
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
V67 Zibaldone and scribes LoRA for Flux
