# Low Learning Rate Optimization

A large language model fine-tuned on the Dans-DiscountModels/pretokenization-test-4 dataset, based on the THUDM/GLM-4-32B-Base-0414 model

A video understanding model fine-tuned based on MCG-NJU/videomae-base, trained on an unknown dataset

A version fine-tuned for 1 day using the Docmatix dataset (5% data volume) based on Microsoft's Florence-2 model, suitable for image-text understanding tasks

A Flux LoRA model trained on public domain images, specializing in retro comic-style character depictions

A vision Transformer model fine-tuned on the beans dataset based on google/vit-base-patch16-224-in21k

BERT is a pre-trained language model based on the Transformer architecture, developed by Google. This model excels in various natural language processing tasks, including text classification, question answering, and named entity recognition.

This model is a fine-tuned version of DistilBERT on an unspecified dataset, primarily used for text classification tasks.

BERT is a pre-trained language model based on the Transformer architecture, developed by Google. It understands text through bidirectional context and is suitable for various natural language processing tasks.

KLUE-RoBERTa-large is a Korean pre-trained language model based on the RoBERTa architecture, developed by a Korean research team and optimized for Korean natural language processing tasks.