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Official Code Repository for the paper "Distilling LLM Agent into Small Models with Retrieval and Code Tools"
This repository collects papers for "A Survey on Knowledge Distillation of Large Language Models". We break down KD into Knowledge Elicitation and Distillation Algorithms, and explore the Skill & V…
ShinkaEvolve: Towards Open-Ended and Sample-Efficient Program Evolution
Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.
Universal LLM Deployment Engine with ML Compilation
[ICLR2024 spotlight] OmniQuant is a simple and powerful quantization technique for LLMs.
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
A Tree Search Library with Flexible API for LLM Inference-Time Scaling
Python Implementation of MUVERA (Multi-Vector Retrieval via Fixed Dimensional Encodings)
A blazing fast AI Gateway with integrated guardrails. Route to 200+ LLMs, 50+ AI Guardrails with 1 fast & friendly API.
Research papers and blogs to transition to AI Engineering
Official inference framework for 1-bit LLMs
Awesome Reasoning LLM Tutorial/Survey/Guide
TensorZero is an open-source stack for industrial-grade LLM applications. It unifies an LLM gateway, observability, optimization, evaluation, and experimentation.
🤖 Everything you need to create an LLM Agent—tools, prompts, frameworks, and models—all in one place.
Adding guardrails to large language models.
Flock is a workflow-based low-code platform for rapidly building chatbots, RAG, and coordinating multi-agent teams, powered by LangGraph, Langchain, FastAPI, and NextJS.（Flock 是一个基于workflow工作流的低代码平…
Delivery infrastructure for agents. Arch is a models-native proxy and data plane for agents that handles plumbing work in AI - like agent routing and orchestration, guardrails, zero-code logs and t…
Just like the beloved character Doraemon who pulls out gadgets from his pocket, this agent can dynamically create, save, and utilize its own tools when needed.
🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.