MarkItDown is a lightweight Python utility for converting various files to Markdown for use with LLMs and related text analysis pipelines. To this end, it is most comparable to textract, but with a focus on preserving important document structure and content as Markdown (includin. Use it to build a structured path from fundamentals to hands-on practice.
Tool for generating high-quality synthetic datasets to fine-tune LLMs. Use it to navigate the topic and choose relevant methods, papers or tools.
Mooncake is the serving platform for Kimi, a leading LLM service provided by Moonshot AI. Under real workloads, Mooncake’s innovative architecture enables Kimi to handle 75% more requests while adhering to SLOs. Use it to ground design choices in named patterns, trade-offs and examples.
LLMTools is a user-friendly library for running and finetuning LLMs in low-resource settings. Features include: 🔨 LLM finetuning in 2-bit, 3-bit, 4-bit precision using the ModuLoRA algorithm 🐍 Easy-to-use Python API for quantization, inference, and finetuning 🤖 Modular supp. Use it to navigate the topic and choose relevant methods, papers or tools.
TRL is a cutting-edge library designed for post-training foundation models using advanced techniques like Supervised Fine-Tuning (SFT), Group Relative Policy Optimization (GRPO), and Direct Preference Optimization (DPO). Built on top of the 🤗 Transformers ecosystem, TRL supports. Use it to navigate the topic and choose relevant methods, papers or tools.
StageRAG is a lightweight, production-ready RAG framework designed to give you precise control over the speed-versus-accuracy trade-off. It allows you to build high-factuality applications while gracefully managing uncertainty in LLM responses. Use it to navigate the topic and choose relevant methods, papers or tools.
Simple Python bindings for @ggerganov's llama.cpp library. This package provides:. Use it to ground design choices in named patterns, trade-offs and examples.
Official PyTorch implementation for Extreme Compression of Large Language Models via Additive Quantization. Use it to navigate the topic and choose relevant methods, papers or tools.
Quick Start • Architecture • Training • Validation • Inference • Examples • Configuration • Troubleshooting. Use it to ground design choices in named patterns, trade-offs and examples.
A community-driven hub of 42+ runnable notebooks covering RAG techniques from foundational to cutting-edge - the intuition, the code, and the references to build more accurate, context-rich retrieval systems. Use it as a repeatable review, validation or hardening pass.
This repo collects papers, documents, and codes about model quantization for anyone who wants to research it. We are continuously improving the project. Use it to navigate the topic and choose relevant methods, papers or tools.
MarkItDown is a lightweight Python utility for converting various files to Markdown for use with LLMs and related text analysis pipelines. To this end, it is most comparable to textract, but with a focus on preserving important document structure and content as Markdown (includin. Use it to build a structured path from fundamentals to hands-on practice.
Tool for generating high-quality synthetic datasets to fine-tune LLMs. Use it to navigate the topic and choose relevant methods, papers or tools.
Mooncake is the serving platform for Kimi, a leading LLM service provided by Moonshot AI. Under real workloads, Mooncake’s innovative architecture enables Kimi to handle 75% more requests while adhering to SLOs. Use it to ground design choices in named patterns, trade-offs and examples.
LLMTools is a user-friendly library for running and finetuning LLMs in low-resource settings. Features include: 🔨 LLM finetuning in 2-bit, 3-bit, 4-bit precision using the ModuLoRA algorithm 🐍 Easy-to-use Python API for quantization, inference, and finetuning 🤖 Modular supp. Use it to navigate the topic and choose relevant methods, papers or tools.
TRL is a cutting-edge library designed for post-training foundation models using advanced techniques like Supervised Fine-Tuning (SFT), Group Relative Policy Optimization (GRPO), and Direct Preference Optimization (DPO). Built on top of the 🤗 Transformers ecosystem, TRL supports. Use it to navigate the topic and choose relevant methods, papers or tools.
StageRAG is a lightweight, production-ready RAG framework designed to give you precise control over the speed-versus-accuracy trade-off. It allows you to build high-factuality applications while gracefully managing uncertainty in LLM responses. Use it to navigate the topic and choose relevant methods, papers or tools.
Simple Python bindings for @ggerganov's llama.cpp library. This package provides:. Use it to ground design choices in named patterns, trade-offs and examples.
Official PyTorch implementation for Extreme Compression of Large Language Models via Additive Quantization. Use it to navigate the topic and choose relevant methods, papers or tools.
Quick Start • Architecture • Training • Validation • Inference • Examples • Configuration • Troubleshooting. Use it to ground design choices in named patterns, trade-offs and examples.
A community-driven hub of 42+ runnable notebooks covering RAG techniques from foundational to cutting-edge - the intuition, the code, and the references to build more accurate, context-rich retrieval systems. Use it as a repeatable review, validation or hardening pass.
This repo collects papers, documents, and codes about model quantization for anyone who wants to research it. We are continuously improving the project. Use it to navigate the topic and choose relevant methods, papers or tools.