Rust implementations of vision transformer models

Reddit r/ArtificialInteligence 05/24/26, 12:48 PM Tools

vision-transformer rust deep-learning open-source image-classification transformer

Summary

A Rust crate for building and experimenting with Vision Transformer (ViT) models, providing typed configs, reusable structs, and runnable examples for research and production.

Deep learning in rust, this crate is for building and experimenting with ViT-style image, video, sequence, and self-supervised transformer models in Rust. It provides typed configs, reusable model structs, runnable examples, and shape tests for research prototypes and Rust deep learning projects. Now a Vision Transformer treats an image like a sequence. Normal images have this shape: \[batch, channels, height, width\] The model changes the image into this shape: \[batch, tokens, dim\] The flow is: Split the image into patches. Flatten each patch into one long vector. Project each patch vector into dim. Add position embeddings. Run transformer layers. Pool the tokens. Predict class logits. If you wanna learn more see here: https://github.com/iBz-04/vitch

Original Article

Similar Articles

GitHub - kallewoof/tftf: Transforming Transformers -- ultra light-weight pipeline for enormous transformer model manipulation with minimal overhead

Reddit r/LocalLLaMA

tftf is a lightweight, streaming pipeline for manipulating HuggingFace safetensors models, enabling FP8 dequantisation, LoRA merging, and other operations without loading the full model into memory, minimizing RAM and VRAM overhead.

RyanCodrai/turbovec

GitHub Trending (daily)

turbovec is a Rust vector index with Python bindings implementing Google's TurboQuant algorithm, offering efficient vector search with online ingest, faster-than-FAISS performance, and filtered search capabilities.

Fearless Concurrency on the GPU: Safe GPU inference in Rust, competitive with vLLM/SGLang [R]

Reddit r/MachineLearning

cuTile Rust introduces a tile-based programming model that leverages Rust's ownership to guarantee memory safety and data-race freedom for GPU kernels, and the Grout inference engine built on it achieves competitive throughput with vLLM/SGLang for Qwen3 models.

Building ML framework with Rust and Category Theory

Hacker News Top

This article announces a working draft book 'Category Theory for Tiny ML in Rust' and a public workshop introducing a tiny ML pipeline using Rust and category theory, aimed at making machine learning structure explicit through typed transformations.

HOTPOT-Evolvable Agent Specification Framework

Reddit r/AI_Agents

A new agent specification framework built in Rust, featuring a small binary size, Vuepress integration for documentation, issue persistence for improved code review context, and self-repair capabilities. Compatible with several agent tools and still under development.