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Efficiently Fine-Tune 100+ LLMs in WebUI (ACL 2024)
Download market data from Yahoo! Finance's API
A framework for few-shot evaluation of language models.
OpenChat: Advancing Open-source Language Models with Imperfect Data
A Native-PyTorch Library for LLM Fine-tuning
🤗 Evaluate: A library for easily evaluating machine learning models and datasets.
A multi-purpose LLM framework for RAG and data creation.
부스트캠프 AI Tech - Product Serving 자료
A novel embedding training algorithm leveraging ANN search and achieved SOTA retrieval on Trec DL 2019 and OpenQA benchmarks
Uncertainty quantification with PyTorch
A curated list of awesome instruction tuning datasets, models, papers and repositories.
Source Code of Paper "GPTScore: Evaluate as You Desire"
The Universe of Evaluation. All about the evaluation for LLMs.
Code and Data for "Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering"
Self-Evolved Diverse Data Sampling for Efficient Instruction Tuning
Forked repo from https://github.com/EleutherAI/lm-evaluation-harness/commit/1f66adc
Source code of the paper: RetrievalQA: Assessing Adaptive Retrieval-Augmented Generation for Short-form Open-Domain Question Answering [Findings of ACL 2024]
Implementation of the Paper "Goal-Driven Explainable Clustering via Language Descriptions"
ConvGQR: Generative Query Reformulation for Conversational Search. A codebase for ACL 2023 accepted paper.
Code and data for "KoDialogBench: Evaluating Conversational Understanding of Language Models with Korean Dialogue Benchmark" (LREC-COLING 2024)