Nanbeige4-3B-Thinking is a 3-billion parameter inference model in the fourth-generation Nanbeige large language model family. It achieves advanced inference capabilities by improving data quality and training methods. This model performs excellently in multiple fields such as mathematics, science, creative writing, and tool usage, and supports multi-stage curriculum learning and reinforcement learning training.

Natural Language ProcessingTransformersMultiple Languages

Mira is a text generation model based on the fusion of multiple Gemma 3 27B base models. Through carefully selected training data and specific training methods, it has a unique ability to generate poetic texts. This model performs excellently in role-playing and creative writing, and can generate texts with literary charm according to different system prompts.

Natural Language ProcessingTransformers

Cogito v2 is a generative hybrid inference model fine-tuned by instructions. It uses iterative distillation and amplification training methods and performs excellently in coding, STEM, instruction following, etc. It supports over 30 languages and a 128k context length.

Natural Language ProcessingTransformers

Hunyuan 7B is an open-source bilingual large language model (Chinese and English) by Tencent, featuring optimized data ratios and training methods for robust performance, making it one of the strongest Chinese 7B Dense models available.

Natural Language ProcessingTransformersEnglish

Eagle2 is a high-performance series of vision-language models focused on enhancing model performance through optimized data strategies and training methods. Eagle2-9B is the large model in this series, achieving a good balance between performance and inference speed.

MultimodalTransformersOther

TabPFN is a Transformer-based foundational model for tabular data. Through prior-data-based learning methods, it achieves strong performance on small-scale tabular regression tasks without requiring task-specific training.

AIM-v2 is an image encoder based on the timm library, utilizing distillation training methods, suitable for image feature extraction tasks.

Computer VisionTransformers

This project includes a series of text-to-image generation models based on Flux. Through different training and fusion methods, images with different styles and characteristics are generated. These models focus on generating Japanese-style images of different ages and in different scenarios, providing diverse options for image creation.

Computer VisionGgufEnglish

A fully parameter fine-tuned large language model based on Meta-Llama-3.1-8B architecture, focused on English text and Python code tasks, utilizing diverse data mixture training methods

Natural Language ProcessingGgufEnglish

Minitron-8B-Base is a large language model obtained by pruning Nemotron-4 15B, employing distillation and continuous training methods, saving 40 times the training tokens and 1.8 times the computational cost compared to training from scratch.

Natural Language ProcessingTransformersEnglish

SimPO is a simple and effective preference optimization method that simplifies the alignment process by eliminating the need for a reference model. This method uses the average log probability as an implicit reward and achieves stable training through a length-normalized objective, outperforming existing methods such as DPO in multiple benchmarks.

Natural Language ProcessingTransformers

This is a large Transformer model with 780 million parameters, specifically designed for music generation and transcription tasks, using anticipatory training methods.

Audio ProcessingTransformers

An experimental AI model developed through cutting-edge training methods, focusing on optimizing continuous learning and knowledge absorption capabilities

Natural Language ProcessingTransformersEnglish

MetaCLIP is an implementation of the CLIP framework applied to CommonCrawl data, aiming to reveal CLIP's training data filtering methods

MultimodalTransformers

A BERT-based zero-shot text classification model trained on the UTCD dataset using explicit training methods

Natural Language ProcessingTransformersEnglish

A large English language model pre-trained with masked language modeling objectives, using improved BERT training methods

Natural Language ProcessingJaxEnglish