Alternatives and similar repositories for ado

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

• allenai / easy-to-hard-generalization
  Code for the arXiv preprint "The Unreasonable Effectiveness of Easy Training Data"
  ☆48Updated last year
• john-hewitt / implicit-ins
  Codebase for Instruction Following without Instruction Tuning
  ☆35Updated 10 months ago
• r-three / RAD
  Reference implementation for Reward-Augmented Decoding: Efficient Controlled Text Generation With a Unidirectional Reward Model
  ☆44Updated last year
• casmlab / NPHardEval
  Repository for NPHardEval, a quantified-dynamic benchmark of LLMs
  ☆57Updated last year
• sail-sg / SkyLadder
  The official repository for SkyLadder: Better and Faster Pretraining via Context Window Scheduling
  ☆33Updated this week
• mcleish7 / gemstone-scaling-laws
  ☆27Updated 5 months ago
• limenlp / safer-instruct
  This is the oficial repository for "Safer-Instruct: Aligning Language Models with Automated Preference Data"
  ☆17Updated last year
• likenneth / q_probe
  Q-Probe: A Lightweight Approach to Reward Maximization for Language Models
  ☆41Updated last year
• ahans30 / goldfish-loss
  [NeurIPS 2024] Goldfish Loss: Mitigating Memorization in Generative LLMs
  ☆91Updated 8 months ago
• martin-wey / CodeUltraFeedback
  CodeUltraFeedback: aligning large language models to coding preferences
  ☆71Updated last year
• formll / resolving-scaling-law-discrepancies
  ☆20Updated last year
• locuslab / scaling_laws_data_filtering
  ☆65Updated last year
• hughbzhang / o1_inference_scaling_laws
  Replicating O1 inference-time scaling laws
  ☆89Updated 8 months ago
• HazyResearch / aioli
  Aioli: A unified optimization framework for language model data mixing
  ☆27Updated 6 months ago
• hamishivi / automated-instruction-selection
  Exploration of automated dataset selection approaches at large scales.
  ☆47Updated 4 months ago
• mlfoundations / scaling
  Language models scale reliably with over-training and on downstream tasks
  ☆97Updated last year
• davidbrandfonbrener / color-filter-olmo
  ☆13Updated 3 months ago
• tml-epfl / icl-alignment
  Is In-Context Learning Sufficient for Instruction Following in LLMs? [ICLR 2025]
  ☆31Updated 6 months ago
• RobertCsordas / moeut
  ☆82Updated 11 months ago
• matchten / LoRA-Models-for-SAEs
  Code for reproducing our paper "Low Rank Adapting Models for Sparse Autoencoder Features"
  ☆12Updated 4 months ago
• ContextualAI / CLAIR_and_APO
  Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in Alignment
  ☆60Updated 11 months ago
• katiekang1998 / reasoning_generalization
  ☆34Updated 6 months ago
• TRI-ML / linear_open_lm
  A repository for research on medium sized language models.
  ☆78Updated 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"
  ☆71Updated last year
• googleinterns / localizing-paragraph-memorization
  ☆14Updated last year
• architsharma97 / dpo-rlaif
  ☆99Updated last year
• MLE-Dojo / MLE-Dojo
  ☆61Updated last week
• cmu-l3 / neurips2024-inference-tutorial-code
  NeurIPS 2024 tutorial on LLM Inference
  ☆45Updated 7 months ago
• Asap7772 / understanding-rlhf
  Learning from preferences is a common paradigm for fine-tuning language models. Yet, many algorithmic design decisions come into play. Ou…
  ☆30Updated last year
• JacobPfau / fillerTokens
  ☆67Updated last year