zero-shot-learning 开源项目推荐（552 个）

zhaoxin94 /awesome-domain-adaptation

A collection of AWESOME things about domain adaptation

DSXiangLi /DecryptPrompt

总结Prompt&LLM论文，开源数据&模型，AIGC应用

CVI-SZU /Linly

Chinese-LLaMA 1&2、Chinese-Falcon 基础模型；ChatFlow中文对话模型；中文OpenLLaMA模型；NLP预训练/指令微调数据集

sudharsan13296 /Awesome-Meta-Learning

A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.

sudharsan13296 /Hands-On-Meta-Learning-With-Python

Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow

quqxui /Awesome-LLM4IE-Papers

Awesome papers about generative Information Extraction (IE) using Large Language Models (LLMs)

NVlabs /ODISE

ODISE 的官方 PyTorch 实现：使用文本到图像扩散模型的开放词汇全景分割 [CVPR 2023 Highlight]

sbharadwajj /awesome-zero-shot-learning

A curated list of papers, code and resources pertaining to zero shot learning

ttengwang /Awesome_Prompting_Papers_in_Computer_Vision

计算机视觉和视觉语言学习领域基于预算的论文精选列表。

BatsResearch /bonito

A lightweight library for generating synthetic instruction tuning datasets for your data without GPT.

zhengli97 /Awesome-Prompt-Adapter-Learning-for-VLMs-CLIP

A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.

EnnengYang /Awesome-Model-Merging-Methods-Theories-Applications

大语言模型（LLM）、多模态大语言模型（MLLM）及更广领域的模型合并：方法、理论、应用与机遇。ACM Computing Surveys，2026。

NVlabs /GroupViT

Official PyTorch implementation of GroupViT: Semantic Segmentation Emerges from Text Supervision, CVPR 2022.

lucidrains /x-clip

A concise but complete implementation of CLIP with various experimental improvements from recent papers

kylinyang0 /You-are-Pythonista

汇聚【Python应用】【Python实训】【Python技术分享】等等

clue-ai /PromptCLUE

PromptCLUE, 全中文任务支持零样本学习模型

ChenWu98 /cycle-diffusion

[ICCV 2023] A latent space for stochastic diffusion models

bigscience-workshop /xmtf

Crosslingual Generalization through Multitask Finetuning

CLUEbenchmark /pCLUE

pCLUE: 1000000+多任务提示学习数据集

diffusion-classifier /diffusion-classifier

Diffusion Classifier leverages pretrained diffusion models to perform zero-shot classification without additional training