Topic: captum Goto Github
Some thing interesting about captum
Some thing interesting about captum
captum,Model explainability that works seamlessly with π€ transformers. Explain your transformers model in just 2 lines of code.
User: cdpierse
captum,XAI Tutorial for the Explainable AI track in the ALPS winter school 2021
Organization: copenlu
captum,Collection of NLP model explanations and accompanying analysis tools
Organization: dfki-nlp
captum,Model interpretability for Explainable Artificial Intelligence
User: dg1223
captum,End-to-end toxic Russian comment classification
User: esceptico
Home Page: https://share.streamlit.io/esceptico/toxic/app.py
captum,Interpretability for sequence generation models π π
Organization: inseq-team
Home Page: https://inseq.org
captum,Cyber Security AI Dashboard
User: jihyeonseong
captum, "XAIλ₯Ό μν Attribution Method μ κ·Όλ² λΆμ λ° λν₯ Analysis and Trend of Attribution Methods for XAI" μμ μ¬μ©ν μ½λμ μμλ₯Ό 곡κ°
User: js-yoo
captum,PyTorch Beginner Workshop (Brad Heintz)
User: k-forghani
captum,Collection of associated files for my bachelor thesis
User: lennardzuendorf
Home Page: https://zuendorf.me/projects/thesis
captum,Based on the papers "Interpretability Beyond Feature Attribution: QuantitativeTestingwithConceptActivationVectors(TCAV)" and Captum's instantiation https://captum.ai/docs/captum_insights, we developed this frontend for the Captum project based on the streamlit framework.
User: manyue-zhang
captum,This repository contains the source code for Indoor Scene Detector, a full stack deep learning computer vision application.
User: nicovandenhooff
Home Page: https://www.indoorscenedetector.com/
captum,COVID-19 forecasting model for East Java cities using Joint Learning. My undergrad thesis.
User: r-n
captum,Trained Neural Networks (LSTM, HybridCNN/LSTM, PyramidCNN, Transformers, etc.) & comparison for the task of Hate Speech Detection on the OLID Dataset (Tweets).
User: richouzo
captum,A small repository to test Captum Explainable AI with a trained Flair transformers-based text classifier.
User: robinvanschaik
captum,Deep Classiflie is a framework for developing ML models that bolster fact-checking efficiency. As a POC, the initial alpha release of Deep Classiflie generates/analyzes a model that continuously classifies a single individual's statements (Donald Trump) using a single ground truth labeling source (The Washington Post). For statements the model deems most likely to be labeled falsehoods, the @DeepClassiflie twitter bot tweets out a statement analysis and model interpretation "report"
User: speediedan
Home Page: https://deepclassiflie.org
captum,Deep_classiflie_db is the backend data system for managing Deep Classiflie metadata, analyzing Deep Classiflie intermediate datasets and orchestrating Deep Classiflie model training pipelines. Deep_classiflie_db includes data scraping modules for the initial model data sources. Deep Classiflie depends upon deep_classiflie_db for much of its analytical and dataset generation functionality but the data system is currently maintained as a separate repository here to maximize architectural flexibility. Depending on how Deep Classiflie evolves (e.g. as it supports distributed data stores etc.), it may make more sense to integrate deep_classiflie_db back into deep_classiflie. Currently, deep_classiflie_db releases are synchronized to deep_classiflie releases. To learn more, visit deepclassiflie.org.
User: speediedan
Home Page: https://deepclassiflie.org
captum,Overview of different model interpretability libraries.
User: tannergilbert
Home Page: https://gilberttanner.com/tag/model-interpretation/
captum,OdoriFy is an open-source tool with multiple prediction engines. This is the source code of the webserver.
User: the-ahuja-lab
Home Page: https://odorify.ahujalab.iiitd.edu.in
captum,Interpretable graph classifications using Graph Convolutional Neural Network
User: tskenneth
captum,Interpretability Metrics
User: yuneg11
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