Go ahead and axolotl questions

Train Dense Passage Retriever (DPR) with a single GPU

The paper list of the 86-page paper "The Rise and Potential of Large Language Model Based Agents: A Survey" by Zhiheng Xi et al.

Sharing the learning along the way we been gathering to enable Azure OpenAI at enterprise scale in a secure manner. GPT-RAG core is a Retrieval-Augmented Generation pattern running in Azure, using …

The papers are organized according to our survey: Evaluating Large Language Models: A Comprehensive Survey.

PyTorch deep learning projects made easy.

Leaked GPTs Prompts Bypass the 25 message limit or to try out GPTs without a Plus subscription.

A unified evaluation framework for large language models

[WWW 2022] Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations

RecAlpaca: A simple framework combing Alpaca and Recommendations.

Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"

Instruct-tune LLaMA on consumer hardware

Code for T-Few from "Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning"

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

QLoRA: Efficient Finetuning of Quantized LLMs

[EMNLP 2021] SimCSE: Simple Contrastive Learning of Sentence Embeddings https://arxiv.org/abs/2104.08821

ACL 2022: BRIO: Bringing Order to Abstractive Summarization

MS MARCO(Microsoft Machine Reading Comprehension) is a large scale dataset focused on machine reading comprehension and question answering

Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM

Train transformer language models with reinforcement learning.

Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%

📖 Paper reading list in conversational AI (constantly updating 🤗).

MLNLP社区用来帮助大家避免论文投稿小错误的整理仓库。 Paper Writing Tips

Code for "Never Too Late to Learn: Regularizing Gender bias in Coreference Resolution"