REaLTabFormer
adaptnlp
| REaLTabFormer | adaptnlp | |
|---|---|---|
| 5 | 2 | |
| 183 | 414 | |
| 5.5% | 0.0% | |
| 5.6 | 0.0 | |
| 11 days ago | over 2 years ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | Apache License 2.0 |
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REaLTabFormer
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World Bank Researchers Open Source REaLTabFormer: A Tabular and Relational Synthetic Data Generation Model
Quick Read: https://www.marktechpost.com/2023/02/21/world-bank-researchers-open-source-realtabformer-a-tabular-and-relational-synthetic-data-generation-model/ Paper: https://arxiv.org/pdf/2302.02041.pdf Github: https://github.com/avsolatorio/realtabformer
- REaLTabFormer: Generating realistic synthetic data using GPT in Python
- Show HN: REaLTabFormer – GPT-based synthetic data generator
- [R] [N] REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers
adaptnlp
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Tools to use for Semantic-searching Question Answering System
Check out adaptnlp
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Case Sensitivity using HuggingFace & Google's T5 model (base)
Yes, there are capitals in the tokenizer vocabulary of t5-base and t5-small, so both support capitalization. A few days ago I was using t5-small through adaptnlp for extractive summarization and capitalization was working fine (https://github.com/Novetta/adaptnlp). AdaptNLP is basically just a transformers wrapper, so if you can't figure out a solution, you could just dissect their source code.
What are some alternatives?
ydata-synthetic - Synthetic data generators for tabular and time-series data
Basic-UI-for-GPT-J-6B-with-low-vram - A repository to run gpt-j-6b on low vram machines (4.2 gb minimum vram for 2000 token context, 3.5 gb for 1000 token context). Model loading takes 12gb free ram.
SkinDeep - Get Deinked!!
keytotext - Keywords to Sentences
tdk-demo - This is a collection of TDK demo projects that use different databases and options
fastai - The fastai deep learning library
gector - Official implementation of the papers "GECToR – Grammatical Error Correction: Tag, Not Rewrite" (BEA-20) and "Text Simplification by Tagging" (BEA-21)
browser-ml-inference - Edge Inference in Browser with Transformer NLP model
Transformers-Tutorials - This repository contains demos I made with the Transformers library by HuggingFace.
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
Deep-Learning-Experiments - Videos, notes and experiments to understand deep learning
BLOOM-fine-tuning - Finetune BLOOM