Sent_debias Alternatives
Similar projects and alternatives to sent_debias based on common topics and language
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embedders
With embedders, you can easily convert your texts into sentence- or token-level embeddings within a few lines of code. Use cases for this include similarity search between texts, information extraction such as named entity recognition, or basic text classification.
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AIF360
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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EthicML
Package for evaluating the performance of methods which aim to increase fairness, accountability and/or transparency
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transferlearning
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
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PaddleHelix
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
sent_debias reviews and mentions
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academic ethics issues in NLP
following on from the above, to what extent should we trust big models and the built in biases that they learn from huge scraped datasets? Many current SOTA trends for doing few shot learning on nlp tasks involve fine tuning existing large language models. There are lots of interesting research is going on around understanding and removing these biases like this paper from Liang and Li @ ACL2020. A related point is explainability - again some interesting work going on around things like rationale generation this now somewhat old paper by Lei et al 2016 gives some good context
Stats
pliang279/sent_debias is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of sent_debias is Python.
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