BERT
BERT, short for Bidirectional Encoder Representations from Transformers, is a pretrained language model introduced by researchers at Google Research in 2018.
Transformer Models
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BioBERT
BioBERT (Bidirectional Encoder Representations from Transformers for Biomedical Text Mining) is a domain-specific language model that adapts BERT to biomedicine by continuing its pre-training on large…
Hy4 Preview
Hy4 Preview is an open-weight large language model released by the Tencent Hy Team on August 28, 2026.
Longformer
Longformer is a transformer architecture for processing long documents, introduced by Iz Beltagy, Matthew E. Peters
PaLM
PaLM (Pathways Language Model) is a family of dense, decoder-only large language models developed by Google Research. Google announced the original family on April 4, 2022.
Qwen3.8-Flash-Next
Qwen3.8-Flash-Next is an experimental open-weight multimodal large language model released by Alibaba Group's Qwen team on August 26, 2026.
Rotary Position Embedding
Rotary Position Embedding (RoPE) is a positional encoding method for transformer models that encodes a token's absolute position by rotating its query and key vectors in two-dimensional subspaces
Switch Transformer
The Switch Transformer is a sparsely activated Mixture of Experts (MoE) Transformer architecture introduced by William Fedus, Barret Zoph, and Noam Shazeer at Google in January 2021.
T5 (language model)
T5 (Text-to-Text Transfer Transformer) is a family of transformer-based language models released by Google in 2019-2020 that reframes every natural language processing (NLP) task, classification, translation…