A framework for prompt tuning using Intent-based Prompt Calibration
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Updated
Nov 23, 2024 - Python
A framework for prompt tuning using Intent-based Prompt Calibration
Distilabel is a framework for synthetic data and AI feedback for engineers who need fast, reliable and scalable pipelines based on verified research papers.
Perception toolkit for sim2real training and validation in Unity
DataDreamer: Prompt. Generate Synthetic Data. Train & Align Models. 🤖💤
A lightweight library for generating synthetic instruction tuning datasets for your data without GPT.
Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips
A curated list of awesome projects which use Machine Learning to generate synthetic content.
NVIDIA Deep learning Dataset Synthesizer (NDDS)
Official repository for "Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing". Your efficient and high-quality synthetic data generation pipeline!
SynthDet - An end-to-end object detection pipeline using synthetic data
Augmentation pipeline for rendering synthetic paper printing, faxing, scanning and copy machine processes
Unity's privacy-preserving human-centric synthetic data generator
Random dataframe and database table generator
[IMC 2020 (Best Paper Finalist)] Using GANs for Sharing Networked Time Series Data: Challenges, Initial Promise, and Open Questions
[NeurIPS D&B Track 2024] Official implementation of HumanVid
awesome synthetic (text) datasets
Compose multimodal datasets 🎹
A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.
DataGene - Identify How Similar TS Datasets Are to One Another (by @firmai)
[CVPR 2021] DeFMO: Deblurring and Shape Recovery of Fast Moving Objects
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