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Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching
๐ค Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
๐ A delightful community-driven (with 2,300+ contributors) framework for managing your zsh configuration. Includes 300+ optional plugins (rails, git, macOS, hub, docker, homebrew, node, php, pythonโฆ
A ChatGPT Copilot in Obsidian
Open source implementation of "A Self-Supervised Descriptor for Image Copy Detection" (SSCD).
๐ฅ๐ฅ๐ฅLatest Papers, Codes and Datasets on Vid-LLMs.
๐ฆ๐ Build context-aware reasoning applications
FranzKafkaYu / x-ui
Forked from vaxilu/x-uiLightweight Xray panel with multi-protocol and multi-user on the same port,supports English language and Telegram bot. Easy to use and easy to manage.
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
A web GUI client of Project V which supports VMess, VLESS, SS, SSR, Trojan, Tuic and Juicity protocols. ๐
Empowering everyone to build reliable and efficient software.
A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: ๐บ๐ธ ๐จ๐ณ ๐ฏ๐ต ๐ฎ๐น ๐ฐ๐ท ๐ท๐บ ๐ง๐ท ๐ช๐ธ
Authors official PyTorch implementation of the "Self-Supervised Video Similarity Learning" [CVPRW 2023]
Development and compilation setup for the book versions of MINIX (2.0.0 and 3.1.0) on QEMU
Original Minix 1 sources from the book "Operating Systems: Design and Implementation" 1st ed.
GitHub special files and paths, such as README, LICENSE, .github, docs, dependabot, workflows.
Temporal-Relational CrossTransformers (CVPR 2021)
ChatGLM-6B: An Open Bilingual Dialogue Language Model | ๅผๆบๅ่ฏญๅฏน่ฏ่ฏญ่จๆจกๅ
Open-sourced codes for MiniGPT-4 and MiniGPT-v2 (https://minigpt-4.github.io, https://minigpt-v2.github.io/)
๐งโ๐ซ 60 Implementations/tutorials of deep learning papers with side-by-side notes ๐; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), ganโฆ
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
An annotated implementation of the Transformer paper.
Taming Transformers for High-Resolution Image Synthesis