Kangyeol Kim's starred repositories

langflow

⛓️ Langflow is a visual framework for building multi-agent and RAG applications. It's open-source, Python-powered, fully customizable, model and vector store agnostic.

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magic-animate

[CVPR 2024] MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model

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trl

Train transformer language models with reinforcement learning.

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StableCascade

Official Code for Stable Cascade

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civitai

A repository of models, textual inversions, and more

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automatic

SD.Next: Advanced Implementation of Stable Diffusion and other Diffusion-based generative image models

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OOTDiffusion

Official implementation of OOTDiffusion: Outfitting Fusion based Latent Diffusion for Controllable Virtual Try-on

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IC-Light

More relighting!

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Moore-AnimateAnyone

Character Animation (AnimateAnyone, Face Reenactment)

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sample-app-aoai-chatGPT

Sample code for a simple web chat experience through Azure OpenAI, including Azure OpenAI On Your Data.

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amazon-bedrock-workshop

This is a workshop designed for Amazon Bedrock a foundational model service.

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animatediff-cli-prompt-travel

animatediff prompt travel

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Hotshot-XL

✨ Hotshot-XL: State-of-the-art AI text-to-GIF model trained to work alongside Stable Diffusion XL

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optimum-quanto

A pytorch quantization backend for optimum

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ao

Custom data types and layouts for training and inference

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honeybee

Official implementation of project Honeybee (CVPR 2024)

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Scenimefy

[ICCV 2023] Scenimefy: Learning to Craft Anime Scene via Semi-Supervised Image-to-Image Translation

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diffusion-fast

Faster generation with text-to-image diffusion models.

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imagineapi

The MidJourney API (unofficial)

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Zero2Story

Zero2Story

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stable-diffusion-tritonserver

Deploy stable diffusion model with onnx/tenorrt + tritonserver

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primevue-examples

PrimeVue Example Projects

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llmblueprint

[ICLR 2024] Official code for the paper "LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts"

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face0-sdxl

Unofficial implementation of Face0 with SDXL

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pytest-guide

Pytest guide for unittest users

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