google-research / prompt-tuningLinks
Original Implementation of Prompt Tuning from Lester, et al, 2021
☆693Updated 5 months ago
Alternatives and similar repositories for prompt-tuning
Users that are interested in prompt-tuning are comparing it to the libraries listed below
Sorting:
- Expanding natural instructions☆1,012Updated last year
- Reading list of Instruction-tuning. A trend starts from Natrural-Instruction (ACL 2022), FLAN (ICLR 2022) and T0 (ICLR 2022).☆769Updated 2 years ago
- AutoPrompt: Automatic Prompt Construction for Masked Language Models.☆631Updated 11 months ago
- ☆1,535Updated 2 weeks ago
- Prefix-Tuning: Optimizing Continuous Prompts for Generation☆944Updated last year
- Code repository for supporting the paper "Atlas Few-shot Learning with Retrieval Augmented Language Models",(https//arxiv.org/abs/2208.03…☆547Updated last year
- Fusion-in-Decoder☆582Updated last year
- Contriever: Unsupervised Dense Information Retrieval with Contrastive Learning☆751Updated 2 years ago
- Reproduce results and replicate training fo T0 (Multitask Prompted Training Enables Zero-Shot Task Generalization)☆462Updated 2 years ago
- OpenICL is an open-source framework to facilitate research, development, and prototyping of in-context learning.☆569Updated last year
- ☆348Updated 4 years ago
- Code for T-Few from "Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning"☆456Updated last year
- Prod Env☆427Updated last year
- Accompanying repo for the RLPrompt paper☆345Updated last year
- A research project for natural language generation, containing the official implementations by MSRA NLC team.☆736Updated last year
- [EMNLP 2022] Unifying and multi-tasking structured knowledge grounding with language models☆562Updated 2 years ago
- Papers and Datasets on Instruction Tuning and Following. ✨✨✨☆499Updated last year
- Crosslingual Generalization through Multitask Finetuning☆538Updated 11 months ago
- Human preference data for "Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback"☆1,775Updated 2 months ago
- Few-shot Learning of GPT-3☆353Updated last year
- [ACL 2021] LM-BFF: Better Few-shot Fine-tuning of Language Models https://arxiv.org/abs/2012.15723☆729Updated 2 years ago
- This repository contains code to quantitatively evaluate instruction-tuned models such as Alpaca and Flan-T5 on held-out tasks.☆547Updated last year
- [NeurIPS'22 Spotlight] A Contrastive Framework for Neural Text Generation☆471Updated last year
- This repository contains a collection of papers and resources on Reasoning in Large Language Models.☆564Updated last year
- TruthfulQA: Measuring How Models Imitate Human Falsehoods☆792Updated 7 months ago
- This is the repository of HaluEval, a large-scale hallucination evaluation benchmark for Large Language Models.☆497Updated last year
- ☆444Updated 2 years ago
- [EMNLP 2023] Enabling Large Language Models to Generate Text with Citations. Paper: https://arxiv.org/abs/2305.14627☆495Updated 10 months ago
- Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"☆1,188Updated last year
- Implementation of "The Power of Scale for Parameter-Efficient Prompt Tuning"☆167Updated 3 years ago