knn-transformers
PyTorch + HuggingFace code for RetoMaton: "Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval" (ICML 2022), including an implementation of kNN-LM and kNN-MT
https://github.com/alan-turing-institute/robots-in-disguise
Information and materials for the Turing's "robots-in-disguise" reading group on fundamental AI research.
https://github.com/csinva/tree-prompt
Tree prompting: easy-to-use scikit-learn interface for improved prompting.
https://github.com/bigscience-workshop/petals
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
https://github.com/bigscience-workshop/xmtf
Crosslingual Generalization through Multitask Finetuning
https://github.com/cedrickchee/chatgpt-universe
ChatGPT Universe is fleeting notes on ChatGPT, GPT, and large language models (LLMs)
https://github.com/deepset-ai/farm
:house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.
https://github.com/centre-for-humanities-computing/danish-ner-bias
Investigating bias in Danish language models in Named Entity Recognition (NER). Code from the paper titled "Detecting intersectionality in NER models: A data-driven approach."
llm-math-education
Retrieval augmented generation for middle-school math question answering and hint generation.
FMAT
😷 The Fill-Mask Association Test (FMAT): Measuring Propositions in Natural Language.
polish-nlp-resources
Pre-trained models and language resources for Natural Language Processing in Polish
nlg-metricverse
[COLING22] An End-to-End Library for Evaluating Natural Language Generation
https://github.com/alfa-group/code-representations-ml-brain
[NeurIPS 2022] "Convergent Representations of Computer Programs in Human and Artificial Neural Networks" by Shashank Srikant*, Benjamin Lipkin*, Anna A. Ivanova, Evelina Fedorenko, Una-May O'Reilly.
awesome-llm-papers.github.io
A curated collection of the most impactful papers, tools, and resources on Large Language Models (LLMs). Continuously updated to help researchers, developers, and enthusiasts stay on top of LLM advancements.
https://github.com/safellmhub/hguard-go
Guardrails for LLMs: detect and block hallucinated tool calls to improve safety and reliability.