Hackernews posts about Transformer
Transformer is a type of neural network architecture designed for natural language processing tasks that relies on self-attention mechanisms to process input sequences in parallel.
Related:
Apple
- Oasis: A Universe in a Transformer (oasis-model.github.io)
- Oasis: A Universe in a Transformer (oasis-model.github.io)
- Don't Look Twice: Faster Video Transformers with Run-Length Tokenization (rccchoudhury.github.io)
- Grant Sanderson: Visualizing transformers and attention [video] (www.youtube.com)
- Oasis: A Universe in a Transformer (www.decart.ai)
- Oasis: A Universe in a Transformer (Playable Demo) (oasis.decart.ai)
- Largest transformer maker warns of supply crunch (www.ft.com)
- Real-Time Market Data Forecasting with Transformer Models (jdsemrau.substack.com)
- ASIC for Transformers (www.tomshardware.com)
- Tiny Transformers Excel at Sentence Compression (arxiv.org)
- EasyAnimate: Long Video Generation Based on Transformer Architecture (easyanimate.github.io)
- Transformer Circuits Thread (transformer-circuits.pub)
- An Analogy for Understanding Transformers (2023) (www.lesswrong.com)
- ALTA: Compiler-Based Analysis of Transformers (arxiv.org)
- Transformer Interpretability (arena3-chapter1-transformer-interp.streamlit.app)
- In-Context LoRA for Diffusion Transformers (ali-vilab.github.io)
- Training-Free Prompting for Diffusion Transformers (synthical.com)
- Transformers Are Efficient Compilers, Provably (arxiv.org)