Alternatives and similar repositories for soft-prompt-tuning:

Users that are interested in soft-prompt-tuning are comparing it to the libraries listed below

• Spico197 / awesome-lm-evaluation
  🩺 A collection of ChatGPT evaluation reports on various bechmarks.
  ☆48Updated 2 years ago
• HKUNLP / icl-ceil
  [ICML 2023] Code for our paper “Compositional Exemplars for In-context Learning”.
  ☆99Updated 2 years ago
• shmsw25 / Channel-LM-Prompting
  An original implementation of "Noisy Channel Language Model Prompting for Few-Shot Text Classification"
  ☆131Updated 3 years ago
• xu1998hz / InstructScore_SEScore3
  First explanation metric (diagnostic report) for text generation evaluation
  ☆61Updated last month
• Zeng-WH / Prompt-Tuning
  Implementation of "The Power of Scale for Parameter-Efficient Prompt Tuning"
  ☆57Updated 2 years ago
• prakharguptaz / Instructdial
  Code for the paper Code for the paper InstructDial: Improving Zero and Few-shot Generalization in Dialogue through Instruction Tuning
  ☆100Updated last year
• WadeYin9712 / Dynosaur
  Code and data for "Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation" (EMNLP 2023)
  ☆63Updated last year
• GaryYufei / PromDA
  Source code for ACL 2022 Paper "Prompt-based Data Augmentation for Low-Resource NLU Tasks"
  ☆69Updated 2 years ago
• allenai / natural-instructions-v1
  Benchmarking Generalization to New Tasks from Natural Language Instructions
  ☆26Updated 3 years ago
• realtimeqa / realtimeqa_public
  ☆73Updated last year
• corolla-johnson / mkultra
  Prompt tuning toolkit for GPT-2 and GPT-Neo
  ☆88Updated 3 years ago
• Yushi-Hu / IC-DST
  Code base of In-Context Learning for Dialogue State tracking
  ☆45Updated last year
• hkust-nlp / felm
  Github repository for "FELM: Benchmarking Factuality Evaluation of Large Language Models" (NeurIPS 2023)
  ☆58Updated last year
• krystalan / chatgpt_as_nlg_evaluator
  Technical Report: Is ChatGPT a Good NLG Evaluator? A Preliminary Study
  ☆43Updated 2 years ago
• microsoft / HaDes
  Token-level Reference-free Hallucination Detection
  ☆94Updated last year
• mireshghallah / mixmatch
  Repository for ACL 2022 paper Mix and Match: Learning-free Controllable Text Generation using Energy Language Models
  ☆42Updated 3 years ago
• swj0419 / kNN_prompt
  TBC
  ☆26Updated 2 years ago
• lemaoliu / retrieval-generation-reading-list
  This project maintains a reading list for general text generation tasks
  ☆65Updated 3 years ago
• orhonovich / instruction-induction
  ☆64Updated 2 years ago
• Abbey4799 / CELLO
  Code and data for the paper "Can Large Language Models Understand Real-World Complex Instructions?"(AAAI2024)
  ☆48Updated last year
• littlehacker26 / Discriminator-Cooperative-Unlikelihood-Prompt-Tuning
  The code implementation of the EMNLP2022 paper: DisCup: Discriminator Cooperative Unlikelihood Prompt-tuning for Controllable Text Gene…
  ☆26Updated last year
• Yale-LILY / ROSE
  ☆38Updated last year
• OhadRubin / EPR
  ☆61Updated 2 years ago
• thunlp / Prompt-Transferability
  On Transferability of Prompt Tuning for Natural Language Processing
  ☆99Updated 11 months ago
• jzbjyb / ReAtt
  Retrieval as Attention
  ☆83Updated 2 years ago
• thu-coai / PPT
  Official Code for "PPT: Pre-trained Prompt Tuning for Few-shot Learning". ACL 2022
  ☆108Updated 2 years ago
• amazon-science / dse
  ☆43Updated last year
• yinzhangyue / SelfAware
  Do Large Language Models Know What They Don’t Know?
  ☆92Updated 5 months ago
• princeton-nlp / TRIME
  [EMNLP 2022] Training Language Models with Memory Augmentation https://arxiv.org/abs/2205.12674
  ☆196Updated last year
• princeton-nlp / c-sts
  [EMNLP 2023] C-STS: Conditional Semantic Textual Similarity
  ☆70Updated 11 months ago