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A curated list of Large Language Model with RAG
Lightning-fast serving engine for any AI model of any size. Flexible. Easy. Enterprise-scale.
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
Karras et al. (2022) diffusion models for PyTorch
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
StyleTTS 2: Towards Human-Level Text-to-Speech through Style Diffusion and Adversarial Training with Large Speech Language Models
Tensorflow implementations of Diffusion models (DDPM, DDIM)
Devika is an Agentic AI Software Engineer that can understand high-level human instructions, break them down into steps, research relevant information, and write code to achieve the given objective…
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
The official training/validation/test dataset repository for the SOTA? task as SimpleText Task4@CLEF2024
A large-scale text-to-image prompt gallery dataset based on Stable Diffusion
Implementation of Denoising Diffusion Probabilistic Model in Pytorch
A library to generate LaTeX expression from Python code.
Beyond the Imitation Game collaborative benchmark for measuring and extrapolating the capabilities of language models
A basic implementation of ontologies and knowledge graphs.
Knowledge Graph for Legal Documents using Litigation Releases from the SEC website. Classifies into different crimes, extracts relevant information (violator, violation, action taken by authorities…
🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
The world’s fastest framework for building websites.
Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)
Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
Using Low-rank adaptation to quickly fine-tune diffusion models.
A curation of awesome tools, documents and projects about LLM Security.
The papers are organized according to our survey: Evaluating Large Language Models: A Comprehensive Survey.