Alternatives and similar repositories for TalkToModel

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

• interpretml / TalkToEBM
  A Natural Language Interface to Explainable Boosting Machines
  ☆67Updated 11 months ago
• oxfordinternetinstitute / oxonfair
  Fairness toolkit for pytorch, scikit learn and autogluon
  ☆32Updated 6 months ago
• csinva / imodelsX
  Interpret text data using LLMs (scikit-learn compatible).
  ☆166Updated 2 weeks ago
• AI4LIFE-GROUP / OpenXAI
  OpenXAI : Towards a Transparent Evaluation of Model Explanations
  ☆247Updated 10 months ago
• interpretml / LLM-Tabular-Memorization-Checker
  Testing Language Models for Memorization of Tabular Datasets.
  ☆33Updated 4 months ago
• g8a9 / ferret
  A python package for benchmarking interpretability techniques on Transformers.
  ☆213Updated 8 months ago
• bhaweshiitk / ConformalLLM
  Extending Conformal Prediction to LLMs
  ☆66Updated last year
• AthenaCore / AwesomeResponsibleAI
  A curated list of awesome academic research, books, code of ethics, data sets, institutes, maturity models, newsletters, principles, podc…
  ☆75Updated this week
• vinid / NegotiationArena
  ☆69Updated last year
• microsoft / augmented-interpretable-models
  Interpretable and efficient predictors using pre-trained language models. Scikit-learn compatible.
  ☆42Updated 3 months ago
• alexandrainst / responsible-ai
  Responsible AI knowledge base
  ☆104Updated 2 years ago
• UW-Madison-Lee-Lab / LanguageInterfacedFineTuning
  Code for Language-Interfaced FineTuning for Non-Language Machine Learning Tasks.
  ☆128Updated 7 months ago
• nazneenrajani / interpreting-ml-models-course
  Course for Interpreting ML Models
  ☆52Updated 2 years ago
• abacusai / xai-bench
  XAI-Bench is a library for benchmarking feature attribution explainability techniques
  ☆68Updated 2 years ago
• facebookresearch / ResponsibleNLP
  Repository for research in the field of Responsible NLP at Meta.
  ☆200Updated last month
• stanford-crfm / ecosystem-graphs
  ☆267Updated 5 months ago
• dylan-slack / Fooling-LIME-SHAP
  Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)
  ☆82Updated 2 years ago
• worldbank / REaLTabFormer
  A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.
  ☆230Updated 3 weeks ago
• facebookresearch / nbm-spam
  Training and evaluating NBM and SPAM for interpretable machine learning.
  ☆78Updated 2 years ago
• andreArtelt / ceml
  CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox
  ☆44Updated 3 weeks ago
• csinva / iprompt
  Finding semantically meaningful and accurate prompts.
  ☆46Updated last year
• YilunZhou / ExSum
  Code repository for the NAACL 2022 paper "ExSum: From Local Explanations to Model Understanding"
  ☆64Updated 3 years ago
• tabularis-ai / be_great
  A novel approach for synthesizing tabular data using pretrained large language models
  ☆310Updated last month
• hendrycks / ethics
  Aligning AI With Shared Human Values (ICLR 2021)
  ☆286Updated 2 years ago
• amit-sharma / chatgpt-causality-pairs
  Solving the causality pairs challenge (does A cause B) with ChatGPT
  ☆77Updated last year
• simsal0r / mixture-of-decision-trees
  Mixture of Decision Trees for Interpretable Machine Learning
  ☆11Updated 3 years ago
• neelsjain / BYOD
  The Official Repository for "Bring Your Own Data! Self-Supervised Evaluation for Large Language Models"
  ☆108Updated last year
• carla-recourse / CARLA
  CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
  ☆291Updated last year
• minalee-research / coauthor-interface
  ☆95Updated last year
• microsoft / mechanistic-error-probe
  A mechanistic approach for understanding and detecting factual errors of large language models.
  ☆46Updated 11 months ago