Stars
Qwen3 is the large language model series developed by Qwen team, Alibaba Cloud.
Fine-tune LLMs for free with 100+ Notebooks on Google Colab, Kaggle, and more.
Knowledge Agents and Management in the Cloud
Open-source unified multimodal model
FD97Evaluation software used in the Text Retrieval Conference
AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data…
Pocket Flow: Codebase to Tutorial
State-of-the-Art Text Embeddings
21 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
A curated list of 120+ LLM libraries category wise.
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
Granite Snack Cookbook -- easily consumable recipes (python notebooks) that showcase the capabilities of the Granite models
💡 All-in-one open-source AI framework for semantic search, LLM orchestration and language model workflows
A playbook for systematically maximizing the performance of deep learning models.
Repo designed to help learn the Hugging Face ecosystem (transformers, datasets, accelerate + more).
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Janus-Series: Unified Multimodal Understanding and Generation Models
Red light green light game from squid game made using JavaScript and Three.js https://divyansh6799.github.io/Squid-game/
Unify Efficient Fine-tuning of RAG Retrieval, including Embedding, ColBERT, ReRanker.
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Fine-Tuning Embedding for RAG with Synthetic Data
An open-source ML pipeline development platform
A framework for few-shot evaluation of language models.
Gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls)
Code repo for the ICML 2024 paper "Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation"
A course on aligning smol models.
Retrieval and Retrieval-augmented LLMs