tatsu-lab / alpaca_evalLinks
An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.
☆1,785Updated 6 months ago
Alternatives and similar repositories for alpaca_eval
Users that are interested in alpaca_eval are comparing it to the libraries listed below
Sorting:
- Measuring Massive Multitask Language Understanding | ICLR 2021☆1,447Updated 2 years ago
- Doing simple retrieval from LLM models at various context lengths to measure accuracy☆1,923Updated 10 months ago
- Benchmarking large language models' complex reasoning ability with chain-of-thought prompting☆2,737Updated 11 months ago
- The official GitHub page for the survey paper "A Survey on Evaluation of Large Language Models".☆1,542Updated last month
- 800,000 step-level correctness labels on LLM solutions to MATH problems☆2,018Updated 2 years ago
- A Comprehensive Benchmark to Evaluate LLMs as Agents (ICLR'24)☆2,676Updated 5 months ago
- Holistic Evaluation of Language Models (HELM) is an open source Python framework created by the Center for Research on Foundation Models …☆2,319Updated last week
- Human preference data for "Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback"☆1,760Updated 3 weeks ago
- This includes the original implementation of SELF-RAG: Learning to Retrieve, Generate and Critique through self-reflection by Akari Asai,…☆2,123Updated last year
- A family of open-sourced Mixture-of-Experts (MoE) Large Language Models☆1,555Updated last year
- Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"☆1,183Updated last year
- A simulation framework for RLHF and alternatives. Develop your RLHF method without collecting human data.☆816Updated last year
- YaRN: Efficient Context Window Extension of Large Language Models☆1,511Updated last year
- A framework for the evaluation of autoregressive code generation language models.☆958Updated last week
- A library with extensible implementations of DPO, KTO, PPO, ORPO, and other human-aware loss functions (HALOs).☆865Updated 2 weeks ago
- AgentTuning: Enabling Generalized Agent Abilities for LLMs☆1,451Updated last year
- Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them☆500Updated last year
- AllenAI's post-training codebase☆3,044Updated this week
- Implementation of the training framework proposed in Self-Rewarding Language Model, from MetaAI☆1,392Updated last year
- [ACL2023] We introduce LLM-Blender, an innovative ensembling framework to attain consistently superior performance by leveraging the dive…☆949Updated 8 months ago
- [NeurIPS 2024] SimPO: Simple Preference Optimization with a Reference-Free Reward☆904Updated 4 months ago
- ☆752Updated last year
- A library for advanced large language model reasoning☆2,174Updated last month
- The papers are organized according to our survey: Evaluating Large Language Models: A Comprehensive Survey.☆776Updated last year
- This repository contains code to quantitatively evaluate instruction-tuned models such as Alpaca and Flan-T5 on held-out tasks.☆545Updated last year
- LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.☆711Updated 9 months ago
- Aligning Large Language Models with Human: A Survey☆730Updated last year
- TruthfulQA: Measuring How Models Imitate Human Falsehoods☆760Updated 5 months ago
- Reference implementation for DPO (Direct Preference Optimization)☆2,630Updated 11 months ago
- The official implementation of Self-Play Fine-Tuning (SPIN)☆1,172Updated last year