Jit-Roy / WeeLLM

WeeLLM runs large diffusion models with as little as 4 GB of VRAM, without any quantization. It dynamically determines how many layers can fit within the available VRAM and streams the text encoder and transformer layers to the GPU layer by layer, enabling inference on hardware with limited VRAM. It supports both safetensors and GGUF models.

PaddlePaddle / FastDeploy

High-performance Inference and Deployment Toolkit for LLMs and VLMs based on PaddlePaddle

lihanghang / NLP-Knowledge-Graph

自然语言处理、知识图谱、大语言模型，Agent等技术的前沿追踪、研究与应用。

AgentEra / Agently

[GenAI Application Development Framework] 🚀 Build GenAI application quick and easy 💬 Easy to interact with GenAI agent in code using structure data and chained-calls syntax 🧩 Use Event-Driven Flow *TriggerFlow* to manage complex GenAI working logic 🔀 Switch to any model without rewrite application code

jhawthorn / vernier

📏 next generation CRuby profiler

bernie-g / geckolib

GeckoLib is an animation engine for Minecraft mods, with support for complex 3D keyframe-based animations, numerous easings, concurrent animation support, sound and particle keyframes, event keyframes, math-based animations, and more. Available for all major modloaders.

GubernievS / AntiZapret-VPN

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ernie-research / FoR-T2I

Official repository of FoR-T2I, a benchmark evaluating T2I models from a different perspective.

AcademiaSD / AcademiaSD_LoRAlab-TrainerStudio

Train LoRAs for Qwen-Image 2.1, FLUX.2 Klein 9B, FLUX.3 Image Klein, Krea 2, Z-Image, MOSS-Image, ERNIE-Image, Ideogram 4, Anima, SDXL (Pony, Illustrious, NoobAI), LTX 2.3, MiniMax-H3, and more on NVIDIA GPUs from 4–8 GB VRAM. One install, one launcher, NF4 models. Windows, Linux and RunPod.

legritos / tfbert-xla-multigpu

TensorFlow 1.x BERT Training with Multi-GPU Gradient Accumulation XLA Mixed Precision 2026

ernie-research / CoVisco

official implementation of CoVisco: Codec-Native Vision Encoder with Native Token Compression for Efficient Unified Visual Understanding

jeinlee1991 / chinese-llm-benchmark

非线智能 NoneLinear - ReLE评测：中文AI大模型能力评测（持续更新）：目前已囊括374个大模型，覆盖chatgpt、gpt-5.4、谷歌gemini-3.1-pro、Claude-4.6、文心ERNIE-X1.1、ERNIE-5.0、qwen3.6-max、qwen3.6-plus、百川、讯飞星火、商汤senseChat等商用模型， 以及step3.5-flash、kimi-k2.6、ernie4.5、MiniMax-M2.7、deepseek-v4、Qwen3.6、llama4、智谱GLM-5.1、MiMo-V2、LongCat、gemma4、mistral等开源大模型。不仅提供排行榜，也提供规模超200万的大模型缺陷库！方便广大社区研究分析、改进大模型。