Code and documentation to train Stanford's Alpaca models, and generate the data.
-
Updated
Jul 17, 2024 - Python
Code and documentation to train Stanford's Alpaca models, and generate the data.
An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
✨✨Latest Advances on Multimodal Large Language Models
An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.
An Open-sourced Knowledgable Large Language Model Framework.
Must-read Papers on LLM Agents.
PhoGPT: Generative Pre-training for Vietnamese (2023)
A simulation framework for RLHF and alternatives. Develop your RLHF method without collecting human data.
A collection of open-source dataset to train instruction-following LLMs (ChatGPT,LLaMA,Alpaca)
A collection of ChatGPT and GPT-3.5 instruction-based prompts for generating and classifying text.
This repository collects papers for "A Survey on Knowledge Distillation of Large Language Models". We break down KD into Knowledge Elicitation and Distillation Algorithms, and explore the Skill & Vertical Distillation of LLMs.
Reading list of Instruction-tuning. A trend starts from Natrural-Instruction (ACL 2022), FLAN (ICLR 2022) and T0 (ICLR 2022).
BigCodeBench: Benchmarking Code Generation Towards AGI
Code for "Lion: Adversarial Distillation of Proprietary Large Language Models (EMNLP 2023)"
Finetune LLaMA-7B with Chinese instruction datasets
Code and models of MOCA (Modular Object-Centric Approach) proposed in "Factorizing Perception and Policy for Interactive Instruction Following" (ICCV 2021). We address the task of long horizon instruction following with a modular architecture that decouples a task into visual perception and action policy prediction.
[ICLR 2024] Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models
[NeurIPS'23] "MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing".
Code for "FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models (ACL 2024)"
EditWorld: Simulating World Dynamics for Instruction-Following Image Editing
Add a description, image, and links to the instruction-following topic page so that developers can more easily learn about it.
To associate your repository with the instruction-following topic, visit your repo's landing page and select "manage topics."