[ECCV 2024] Official PyTorch implementation of RoPE-ViT "Rotary Position Embedding for Vision Transformer"
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Updated
Oct 29, 2025 - Python
[ECCV 2024] Official PyTorch implementation of RoPE-ViT "Rotary Position Embedding for Vision Transformer"
[ICLR 2024] CLEX: Continuous Length Extrapolation for Large Language Models
[ECCV 2026] Official implementation of "MemRoPE: Training-Free Infinite Video Generation via Evolving Memory Tokens"
One Diffusion model implementation base on LibTorch
CoPE: Clipped RoPE as A Scalable Free Lunch for Long Context LLMs
PyTorch implementation of Rotary Spatial Embeddings
Decoder-only transformer for molecule generation (SMILES representation).
Image Captioning With MobileNet-LLaMA 3
This repository contains a lightweight PyTorch implementation of Qwen 3-style transformer components in qwen3_from_scratch.py.
面向 Transformer 推理的可验证 Triton 融合算子与 torch.library 集成
A clean, efficient implementation of Rotary Positional Embeddings (RoPE) for transformers, with support for advanced variants like YARN scaling.
Transformer Models for Humorous Text Generation. Fine-tuned on Russian jokes dataset with ALiBi, RoPE, GQA, and SwiGLU.Plus a custom Byte-level BPE tokenizer.
Machine Learning from scratch in C
Decoder-only LLM trained on the Harry Potter books.
minimal Implementation of qwen 3 from scratch including both dense and moe model architectures
RootMeanSquareNorm + Rotary Position Embedding - Triton Kernel Optimization
A from-scratch implementation of a T5 model modified with Rotary Position Embeddings (RoPE). This project includes the code for pre-training on the C4 dataset in streaming mode with Flash Attention 2.
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