파인튜닝, 학습 및 데이터
Megatron-LM
NVIDIA/Megatron-LM
Ongoing research training transformer models at scale
★ 17.2K⑂ 4.3KPython
ToolAI.io · GitHub 채널
GitHub의 새로운 AI 프로젝트
GitHub에서 새로 추가된 오픈 소스 AI 프로젝트를 살펴보고, 저장소 정보, 설정 안내, 라이선스 및 관련 리소스를 확인하세요.
공개 리포지토리 데이터
프로젝트 색인
파인튜닝, 학습 및 데이터
generative-ai-for-beginners
microsoft/generative-ai-for-beginners
21 Lessons, Get Started Building with Generative AI
★ 113.5K⑂ 60.9KJupyter Notebook
파인튜닝, 학습 및 데이터
Paddle
PaddlePaddle/Paddle
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
★ 24K⑂ 6KC++
파인튜닝, 학습 및 데이터
aikit
kaito-project/aikit
🏗️ Fine-tune, build, and deploy open-source LLMs easily!
★ 535⑂ 57Go
파인튜닝, 학습 및 데이터
DeepSpeed
deepspeedai/deepspeed
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
★ 43K⑂ 4.9KPython
에이전트 및 멀티 에이전트
Flyte 2: Dynamic, Resilient AI Orchestration
flyteorg/flyte
Flyte is an open-source orchestration framework for reliably building, scaling, and deploying machine learning pipelines, models, and agents using pure Python.
★ 7.2K⑂ 861Go
에이전트 및 멀티 에이전트
LlamaIndex
run-llama/llama_index
LlamaIndex is an open-source Python data framework for building LLM applications with private data, offering data connectors, indexing structures, and advanced retrieval interfaces. It is complemented by LlamaParse, an enterprise platform for agentic OCR, parsing, extraction, and indexing.
★ 51.4K⑂ 7.9KPython
파인튜닝, 학습 및 데이터
Oumi: Open-Source Foundation Model Training, Evaluation, Inference, and Deployment
oumi-ai/oumi
Oumi is a Python-based platform for preparing data, training and fine-tuning open-weight foundation models, evaluating results, running inference, and deploying models. It provides configuration recipes and a consistent CLI for local, cluster, and cloud workflows.
★ 9.4K⑂ 784Python
파인튜닝, 학습 및 데이터
Langfuse
langfuse/langfuse
An open-source LLM engineering platform for tracing, evaluating, debugging, and improving AI applications, with prompt management, datasets, metrics, a playground, APIs, and managed or self-hosted deployment options.
★ 32.4K⑂ 3.5KTypeScript
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