KitanaQA
OpenAttack
Our great sponsors
| KitanaQA | OpenAttack | |
|---|---|---|
| 1 | 1 | |
| 57 | 652 | |
| - | 2.5% | |
| 0.0 | 0.0 | |
| 9 months ago | 9 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
KitanaQA
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Ask HN: Who is hiring? (February 2021)
Searchable.ai | Full Stack Engineer | Full Time | Remote U.S.
We help our users find their stuff wherever it's stored as we build the future of enterprise search.
We are hiring a full-stack engineer with Rails experience to join our growing engineering team. Our stack includes: Rails, Electron, Webpack, PostgreSQL, Elasticsearch & Kubernetes.
This position will also have the opportunity to help integrate our research teams' SOTA work into our product to help users ask questions across their files (see: https://github.com/searchableai/kitanaqa).
Full description here: https://www.searchable.ai/full-stack-engineer/ and drop us a line at careers at searchable dot ai if you're interested!
OpenAttack
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TextAttack VS OpenAttack - a user suggested alternative
2 projects | 6 Jul 2022
Similar to TextAttack, OpenAttack adopts modular design to assemble various attack models, in order to enable quick implementation of existing or new attack models. But OpenAttack is different from and complementary to TextAttack mainly in the following three aspects: 1) Support for all attacks. TextAttack utilizes a relatively rigorous framework to unify different attack models. However, this framework is naturally not suitable for sentence-level adversarial attacks, an important and typical kind of textual adversarial attacks. Thus, no sentence-level attack models are included in TextAttack. In contrast, OpenAttack adopts a more flexible framework that supports all types of attacks including sentence-level attacks. 2) Multilinguality. TextAttack only covers English textual attacks while OpenAttack supports English and Chinese now. And its extensible design enables quick support for more languages. 3) Parallel processing. Running some attack models maybe very time-consuming, e.g., it takes over 100 seconds to attack an instance with the SememePSO attack model (Zang et al., 2020). To address this issue, OpenAttack additionally provides support for multi-process running of attack models to improve attack efficiency.
What are some alternatives?
TextAttack - TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/
FinBERT-QA - Financial Domain Question Answering with pre-trained BERT Language Model
allennlp - An open-source NLP research library, built on PyTorch.
akvo-flow - A data collection and monitoring tool that works anywhere.
flair - A very simple framework for state-of-the-art Natural Language Processing (NLP)
ozone - Scalable, redundant, and distributed object store for Apache Hadoop
auto-attack - Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"
eClaire - Trello card printer
inltk - Natural Language Toolkit for Indic Languages aims to provide out of the box support for various NLP tasks that an application developer might need
bertviz - BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
jina - ☁️ Build multimodal AI applications with cloud-native stack