Alternatives and similar repositories for LanguageInterfacedFineTuning

Users that are interested in LanguageInterfacedFineTuning are comparing it to the libraries listed below

• neelsjain / BYOD
  The Official Repository for "Bring Your Own Data! Self-Supervised Evaluation for Large Language Models"
  ☆107Updated last year
• WANGXinyiLinda / concept-based-demonstration-selection
  Offical code of the paper Large Language Models Are Implicitly Topic Models: Explaining and Finding Good Demonstrations for In-Context Le…
  ☆75Updated last year
• mlfoundations / rtfm
  Research on Tabular Foundation Models
  ☆56Updated 9 months ago
• zlin7 / UQ-NLG
  ☆99Updated last year
• causalNLP / corr2cause
  Data and code for the Corr2Cause paper (ICLR 2024)
  ☆111Updated last year
• bhaweshiitk / ConformalLLM
  Extending Conformal Prediction to LLMs
  ☆67Updated last year
• dylan-slack / Tablet
  The TABLET benchmark for evaluating instruction learning with LLMs for tabular prediction.
  ☆21Updated 2 years ago
• zeyuyun1 / TransformerVis
  ☆43Updated 3 years ago
• bloomberg / dataless-model-merging
  Code release for Dataless Knowledge Fusion by Merging Weights of Language Models (https://openreview.net/forum?id=FCnohuR6AnM)
  ☆91Updated 2 years ago
• UCSB-NLP-Chang / llm_uncertainty
  ☆36Updated last year
• QingruZhang / PASTA
  PASTA: Post-hoc Attention Steering for LLMs
  ☆122Updated 9 months ago
• p-lambda / incontext-learning
  Experiments and code to generate the GINC small-scale in-context learning dataset from "An Explanation for In-context Learning as Implici…
  ☆108Updated last year
• causalNLP / cladder
  We develop benchmarks and analysis tools to evaluate the causal reasoning abilities of LLMs.
  ☆124Updated last year
• stanfordnlp / axbench
  Stanford NLP Python library for benchmarking the utility of LLM interpretability methods
  ☆128Updated 2 months ago
• xiamengzhou / training_trajectory_analysis
  [ACL 2023]: Training Trajectories of Language Models Across Scales https://arxiv.org/pdf/2212.09803.pdf
  ☆24Updated last year
• kawine / dataset_difficulty
  "Understanding Dataset Difficulty with V-Usable Information" (ICML 2022, outstanding paper)
  ☆87Updated last year
• EvanZhuang / vector-icl
  Official implementation of Vector-ICL: In-context Learning with Continuous Vector Representations (ICLR 2025)
  ☆20Updated 3 months ago
• Thartvigsen / GRACE
  [NeurIPS'23] Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors
  ☆79Updated 8 months ago
• roeehendel / icl_task_vectors
  ☆97Updated last year
• jonhue / activeft
  PyTorch library for Active Fine-Tuning
  ☆91Updated last week
• Varal7 / conformal-language-modeling
  Conformal Language Modeling
  ☆32Updated last year
• guy-dar / embedding-space
  ☆54Updated 2 years ago
• microsoft / mechanistic-error-probe
  A mechanistic approach for understanding and detecting factual errors of large language models.
  ☆47Updated last year
• prateeky2806 / ties-merging
  ☆189Updated last year
• csinva / interpretable-embeddings
  Interpretable text embeddings by asking LLMs yes/no questions (NeurIPS 2024)
  ☆43Updated 10 months ago
• llm-merging / LLM-Merging
  LLM-Merging: Building LLMs Efficiently through Merging
  ☆203Updated 11 months ago
• AnanyaKumar / transfer_learning
  Framework code with wandb, checkpointing, logging, configs, experimental protocols. Useful for fine-tuning models or training from scratc…
  ☆152Updated 2 years ago
• HazyResearch / skill-it
  Skill-It! A Data-Driven Skills Framework for Understanding and Training Language Models
  ☆47Updated last year
• abhishekpanigrahi1996 / transformer_in_transformer
  ☆45Updated last year
• LoryPack / LLM-LieDetector
  Code for the ICLR 2024 paper "How to catch an AI liar: Lie detection in black-box LLMs by asking unrelated questions"
  ☆72Updated last year