txsun1997 / Black-Box-TuningLinks
ICML'2022: Black-Box Tuning for Language-Model-as-a-Service & EMNLP'2022: BBTv2: Towards a Gradient-Free Future with Large Language Models
☆272Updated 3 years ago
Alternatives and similar repositories for Black-Box-Tuning
Users that are interested in Black-Box-Tuning are comparing it to the libraries listed below
Sorting:
- An original implementation of "MetaICL Learning to Learn In Context" by Sewon Min, Mike Lewis, Luke Zettlemoyer and Hannaneh Hajishirzi☆273Updated 2 years ago
- Implementation of ICML 23 Paper: Specializing Smaller Language Models towards Multi-Step Reasoning.☆132Updated 2 years ago
- ☆177Updated last year
- 🎁[ChatGPT4NLU] A Comparative Study on ChatGPT and Fine-tuned BERT☆192Updated 2 years ago
- 🐋 An unofficial implementation of Self-Alignment with Instruction Backtranslation.☆137Updated 8 months ago
- ACL'23: Unified Demonstration Retriever for In-Context Learning☆38Updated 2 years ago
- Paper collections of retrieval-based (augmented) language model.☆232Updated last year
- ☆64Updated 3 years ago
- [EMNLP 2022] Training Language Models with Memory Augmentation https://arxiv.org/abs/2205.12674☆195Updated 2 years ago
- contrastive decoding☆206Updated 3 years ago
- Released code for our ICLR23 paper.☆66Updated 2 years ago
- ☆282Updated last year
- Must-read Papers of Parameter-Efficient Tuning (Delta Tuning) Methods on Pre-trained Models.☆286Updated 2 years ago
- ☆351Updated 4 years ago
- [NeurIPS'22 Spotlight] Data and code for our paper CoNT: Contrastive Neural Text Generation☆152Updated 2 years ago
- [ICLR 2022] Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners☆130Updated 3 years ago
- Implementation of "The Power of Scale for Parameter-Efficient Prompt Tuning"☆167Updated 4 years ago
- Must-read papers on improving efficiency for pre-trained language models.☆105Updated 3 years ago
- Repository for Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning☆168Updated last year
- [ACL 2022] Structured Pruning Learns Compact and Accurate Models https://arxiv.org/abs/2204.00408☆198Updated 2 years ago
- MEND: Fast Model Editing at Scale☆258Updated 2 years ago
- ☆88Updated 3 years ago
- Code for the ACL-2022 paper "Knowledge Neurons in Pretrained Transformers"☆173Updated last year
- ☆55Updated last year
- [ICML 2023] Code for our paper “Compositional Exemplars for In-context Learning”.☆102Updated 2 years ago
- ☆143Updated 2 years ago
- Code for ACL2023 paper: Pre-Training to Learn in Context☆106Updated last year
- Implementation of "The Power of Scale for Parameter-Efficient Prompt Tuning"☆59Updated 3 years ago
- ☆33Updated 4 years ago
- ☆43Updated 2 years ago