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🦜🔗 Build context-aware reasoning applications
A latent text-to-image diffusion model
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
Data and code behind the articles and graphics at FiveThirtyEight
Natural Language Processing Tutorial for Deep Learning Researchers
High-Resolution Image Synthesis with Latent Diffusion Models
YSDA course in Natural Language Processing
FaceChain is a deep-learning toolchain for generating your Digital-Twin.
Inpaint anything using Segment Anything and inpainting models.
[NeurIPS 2024 Best Paper][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An *ult…
The image prompt adapter is designed to enable a pretrained text-to-image diffusion model to generate images with image prompt.
推荐系统入门教程，在线阅读地址：https://datawhalechina.github.io/fun-rec/
Approaching (Almost) Any Machine Learning Problem中译版，在线文档地址：https://ytzfhqs.github.io/AAAMLP-CN/
Official Pytorch Implementation for "MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation" presenting "MultiDiffusion" (ICML 2023)
Concept Sliders for Precise Control of Diffusion Models
A prompting enhancement library for transformers-type text embedding systems
Huggingface-compatible SDXL Unet implementation that is readily hackable
A Framework Code of Reviewing Stable Diffusion Checkpoint
AMeThyst: Art Metrics Tools for hypothesis test
