Stars
A continuously updated collection of papers on agentic SE
yKvD89Sri8 / Awesome-LLM-Uncertainty-Reliability-Robustness
Forked from jxzhangjhu/Awesome-LLM-Uncertainty-Reliability-RobustnessAwesome-LLM-Robustness: a curated list of Uncertainty, Reliability and Robustness in Large Language Models
A survey of privacy problems in Large Language Models (LLMs). Contains summary of the corresponding paper along with relevant code
Awesome-LLM: a curated list of Large Language Model
Latex template for a TUM dissertation/PhD thesis
bigcode-project / Megatron-LM
Forked from NVIDIA/Megatron-LMOngoing research training transformer models 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.
hitum-dev / Awesome-LLM
Forked from Hannibal046/Awesome-LLMAwesome-LLM: a curated list of Large Language Model
A reading list for large models safety, security, and privacy (including Awesome LLM Security, Safety, etc.).
Holistic Evaluation of Language Models (HELM) is an open source Python framework created by the Center for Research on Foundation Models (CRFM) at Stanford for holistic, reproducible and transparen…
yKvD89Sri8 / honest_llama
Forked from hitum-dev/honest_llamaInference-Time Intervention: Eliciting Truthful Answers from a Language Model
Inference-Time Intervention: Eliciting Truthful Answers from a Language Model
LaTeX template to outline and draft academic papers (or theses) in Computer Science (in English and German language)
Instruction Tuning with GPT-4
A collection of resources and papers on Diffusion Models
Pytorch implementation of cnn network
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Code for ICLR2020 paper 'Real or Not Real, that is the Question'
A configurable, tunable, and reproducible library for CTR prediction https://fuxictr.github.io
Code repo for the paper "Privacy-aware Compression for Federated Data Analysis".