captum
Model explainer
Provides tools and algorithms to understand how machine learning models make predictions
Model interpretability and understanding for PyTorch
5k stars
278 watching
503 forks
Language: Python
last commit: about 1 month ago
Linked from 4 awesome lists
feature-attributionfeature-importanceinterpretabilityinterpretable-aiinterpretable-ml
ethicalml/awesome-production-machine-learning
bharathgs/awesome-pytorch-list
kelvins/awesome-mlops
jphall663/awesome-machine-learning-interpretabilityRelated projects:
| Repository | Description | Stars |
|---|---|---|
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 yunjey/pytorch-tutorial | A comprehensive tutorial project that provides code examples for learning PyTorch by implementing various deep learning models and demonstrating their usage. | 30,401 |
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| pytorch/pytorch | A Python library providing tensors and dynamic neural networks with strong GPU acceleration | 84,978 |
 rdspring1/pytorch_gbw_lm | Trains a large-scale PyTorch language model on the 1-Billion Word dataset | 123 |
 codertimo/bert-pytorch | An implementation of Google's 2018 BERT model in PyTorch, allowing pre-training and fine-tuning for natural language processing tasks | 6,251 |
 bentrevett/pytorch-sentiment-analysis | A tutorial repository for building sentiment analysis models with PyTorch using various architectures and techniques. | 4,419 |
 qubvel-org/segmentation_models.pytorch | A comprehensive library for training and applying deep learning models for image segmentation | 9,829 |
 nickjiang2378/vl-interp | This project provides an official PyTorch implementation of a method to interpret and edit vision-language representations to mitigate hallucinations in image captions. | 46 |