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Greko is a friendly AI assistant that runs entirely offline on your phone: nothing you type leaves the device, unless you turn on web search. It can see photos, read your documents, and make Word and Excel files. Greko 2.1 is Greko 2 with much better Greek. **New to Greko? Follow the step-by-step install guide (English and Greek), which shows each Android prompt and what to tap.** The GSM8K and ARC-Easy differences between Greko 2 and 2.1 are within noise (±9 and ±4 points at these sample sizes).
StreetCLIP is a robust foundation model for open-domain image geolocalization and other geographic and climate-related tasks. Trained on an original dataset of 1.1 million street-level urban and rural geo-tagged images, it achieves state-of-the-art performance on multiple open-domain image geolocalization benchmarks in zero-shot, outperforming supervised models trained on millions of images. StreetCLIP is a model pretrained by deriving image captions synthetically from image class labels using a domain-specific caption template. This allows StreetCLIP to transfer its generalized zero-shot learning capabilities to a specific domain (i.e. the domain of image geolocalization). StreetCLIP builds on the OpenAI's pretrained large version of CLIP ViT, using 14x14 pixel patches and images with a 336 pixel side length.
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This LoRA is in pre-alpha stage. It will be a good flux/hidream/chroma LoRA but i need time to do my best. Many checkpoints there are overtrained/broken. I will try to fix that. I am currently experimenting on how to deal with distillation and other hyperparameters. It looks very problematic, even dev2pro is not a solution here. For now it seem that I need to use far bigger rank than 16 or 32. You can find dataset for this lora here: https://huggingface.co/datasets/GeorgyGUF/adidas-tracksuit-with-three-stripes-part1 I will improve this dataset too. You can follow me for updates, I will update this repo everyday and I think it will be renamed too.
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