cablejilo.blogg.se - Jax jumbo sequence game

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LaMDA: Language Models for Dialog Applications Scaling Language Models: Methods, Analysis & Insights from Training GopherĬhain-of-Thought Prompting Elicits Reasoning in Large Language Models Improving language models by retrieving from trillions of tokens WebGPT: Browser-assisted question-answering with human feedback GLaM: Efficient Scaling of Language Models with Mixture-of-Experts Multitask Prompted Training Enables Zero-Shot Task Generalization On the Opportunities and Risks of Foundation Modelsįinetuned Language Models are Zero-Shot Learners

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Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient SparsityĮvaluating Large Language Models Trained on Code ZeRO: Memory Optimizations Toward Training Trillion Parameter Models Megatron-LM: Training Multi-Billion Parameter Language Models Using Model ParallelismĮxploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Language Models are Unsupervised Multitask Learners Improving Language Understanding by Generative Pre-TrainingīERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Add LLM data (Pretraining data/Instruction Tuning data/Chat data/RLHF data) ✨ Contributions WantedĪlso check out the project that I am currently working on: nanoRWKV - The nanoGPT-style implementation of RWKV Language Model (an RNN with GPT-level LLM performance.) Table of Content.

Add some great post about LLM from Yao Fu, Lilian and Andrej.

Add some deploying tools: vLLM, Text Generation Inference.

Add some open-source models: Aquila, Chatglm2, Ultra-LM.

It also contains frameworks for LLM training, tools to deploy LLM, courses and tutorials about LLM and all publicly available LLM checkpoints and APIs.

Here is a curated list of papers about large language models, especially relating to ChatGPT. 🔥 Large Language Models(LLM) have taken the NLP community AI community the Whole World by storm.