Few-shot Learning of GPT-3
☆357Sep 18, 2023Updated 2 years ago
Alternatives and similar repositories for few-shot-learning
Users that are interested in few-shot-learning are comparing it to the libraries listed below
Sorting:
- Code for the paper "True Few-Shot Learning in Language Models" (https://arxiv.org/abs/2105.11447)☆143Oct 25, 2021Updated 4 years ago
- [ACL 2021] LM-BFF: Better Few-shot Fine-tuning of Language Models https://arxiv.org/abs/2012.15723☆730Aug 29, 2022Updated 3 years ago
- Official Pytorch implementation of (Roles and Utilization of Attention Heads in Transformer-based Neural Language Models), ACL 2020☆16Mar 21, 2025Updated 11 months ago
- This repository contains the code for "Exploiting Cloze Questions for Few-Shot Text Classification and Natural Language Inference"☆1,628Jun 12, 2023Updated 2 years ago
- ☆58May 4, 2022Updated 3 years ago
- This repository contains the code for "Generating Datasets with Pretrained Language Models".☆189Aug 17, 2021Updated 4 years ago
- An original implementation of "Noisy Channel Language Model Prompting for Few-Shot Text Classification"☆131Apr 23, 2022Updated 3 years ago
- AutoPrompt: Automatic Prompt Construction for Masked Language Models.☆641Aug 24, 2024Updated last year
- Code for T-Few from "Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning"☆456Sep 6, 2023Updated 2 years ago
- This repository contains the code for "How many data points is a prompt worth?"☆48Apr 7, 2021Updated 4 years ago
- Binary Passage Retriever (BPR) - an efficient passage retriever for open-domain question answering☆175Jun 6, 2021Updated 4 years ago
- Expanding natural instructions☆1,035Dec 11, 2023Updated 2 years ago
- Language model Prompt And Query Archive☆160May 11, 2021Updated 4 years ago
- ☆350Aug 8, 2021Updated 4 years ago
- [TACL 2024] Improving Probability-based Prompt Selection Through Unified Evaluation and Analysis☆11Nov 14, 2024Updated last year
- ☆10Sep 27, 2021Updated 4 years ago
- Coherence boosting: When your pretrained language model is not paying enough attention (ACL 2022) https://arxiv.org/abs/2110.08294☆15Apr 23, 2023Updated 2 years ago
- Ask Me Anything language model prompting☆547Jul 5, 2023Updated 2 years ago
- Few-shot NLP benchmark for unified, rigorous eval☆93Jul 12, 2022Updated 3 years ago
- A codebase for ACL 2023 paper: Mitigating Label Biases for In-context Learning☆10Aug 4, 2023Updated 2 years ago
- ☆89Sep 7, 2022Updated 3 years ago
- Code for our paper: "GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language Models"☆57Apr 23, 2023Updated 2 years ago
- Adversarial Natural Language Inference Benchmark☆399May 12, 2022Updated 3 years ago
- ☆99Jul 25, 2023Updated 2 years ago
- A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.☆938Oct 6, 2022Updated 3 years ago
- LAnguage Model Analysis☆1,390Jul 7, 2024Updated last year
- Code and data to support the paper "PAQ 65 Million Probably-Asked Questions andWhat You Can Do With Them"☆209Aug 31, 2021Updated 4 years ago
- Knowledge Infused Decoding☆71Dec 31, 2023Updated 2 years ago
- This is a repository for the paper on testing inductive bias with scaled-down RoBERTa models.☆21Jan 10, 2022Updated 4 years ago
- ☆131Aug 18, 2022Updated 3 years ago
- ☆329Jun 7, 2021Updated 4 years ago
- Code for: "Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models"☆20Feb 2, 2022Updated 4 years ago
- Data labeling using few shot learning GPT-3.☆25Mar 26, 2023Updated 2 years ago
- Code for NAACL 2022 paper "Reframing Human-AI Collaboration for Generating Free-Text Explanations"☆31Apr 28, 2023Updated 2 years ago
- This repository accompanies our paper “Do Prompt-Based Models Really Understand the Meaning of Their Prompts?”☆85May 10, 2022Updated 3 years ago
- [NeurIPS 2020] "The Lottery Ticket Hypothesis for Pre-trained BERT Networks", Tianlong Chen, Jonathan Frankle, Shiyu Chang, Sijia Liu, Ya…☆142Dec 30, 2021Updated 4 years ago
- This repository contains the FewGLUE dataset for few-shot natural language understanding.☆160Sep 16, 2020Updated 5 years ago
- EMNLP 2021 Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections☆52Sep 15, 2021Updated 4 years ago
- Reproduce results and replicate training fo T0 (Multitask Prompted Training Enables Zero-Shot Task Generalization)☆465Nov 5, 2022Updated 3 years ago