A minimalistic LaTeX template for theses.

A Gradio web UI for Large Language Models.

Unsupervised text tokenizer for Neural Network-based text generation.

Fine-tune open source LLMs with PEFT

Minimal keyword extraction with BERT

This is a Phi-3 book for getting started with Phi-3. Phi-3, a family of open AI models developed by Microsoft. Phi-3 models are the most capable and cost-effective small language models (SLMs) avai…

Universal LLM Deployment Engine with ML Compilation

🔎 SimilaritySearchKit is a Swift package providing on-device text embeddings and semantic search functionality for iOS and macOS applications.

Question-Answering App Over Your Own Data with LLamaindex and ElasticSearch !

Collecting awesome papers of RAG for AIGC. We propose a taxonomy of RAG foundations, enhancements, and applications in paper "Retrieval-Augmented Generation for AI-Generated Content: A Survey".

Examples using MLX Swift

MLX: An array framework for Apple silicon

Finetune Llama 3.1, Mistral, Phi & Gemma LLMs 2-5x faster with 80% less memory

A list of awesome papers and resources of recommender system on large language model (LLM).

Parse files for optimal RAG

LlamaIndex is a data framework for your LLM applications

Implementing a ChatGPT-like LLM in PyTorch from scratch, step by step

🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer

A next-generation curated knowledge sharing platform for data scientists and other technical professions.

(WWW'24) The first RS that tightly combines LLM with ID-based RS.

20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.

Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.

A list of blogs on machine learning and AI 🌟

A customer segmentation project can be approached in multiple ways. In this repository, we will explore advanced techniques for defining clusters and analyzing the results.

Download and preprocess popular sequential recommendation datasets

Curated list of data science interview questions and answers

Streamlit — A faster way to build and share data apps.