transformers-interpret
smaller-transformers
transformers-interpret | smaller-transformers | |
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3 | 1 | |
1,212 | 90 | |
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2.9 | 0.0 | |
8 months ago | almost 2 years ago | |
Jupyter Notebook | Jupyter Notebook | |
Apache License 2.0 | Apache License 2.0 |
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transformers-interpret
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[P] XAI Recipes for the HuggingFace 🤗 Image Classification Models
Very cool, I like seeing this. I also noticed the transformers interpret package has released support for an image classification explainer: https://github.com/cdpierse/transformers-interpret
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Using LIME to explain the predictions from a BERT model, it looks like "the", "and", "or" are "very important" features, and thus I don't think the model is learning anything interesting. Any tips?
You could look at the Transformers Interpret python library: https://github.com/cdpierse/transformers-interpret
- Show HN: Transformers Interpret – Explain and visualize Transformer models
smaller-transformers
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[P] Make LaBSE(language-agnostic BERT Sentence Embedding) smaller for practical usage
Load What You Need: Smaller Versions of Multilingual BERT (Paper: https://arxiv.org/abs/2010.05609, GitHub: https://github.com/Geotrend-research/smaller-transformers)
What are some alternatives?
neuro-symbolic-sudoku-solver - ⚙️ Solving sudoku using Deep Reinforcement learning in combination with powerful symbolic representations.
labse - Language-agnostic BERT Sentence Embedding (LaBSE)
small-text - Active Learning for Text Classification in Python
pytorch-generative - Easy generative modeling in PyTorch.
happy-transformer - Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.
smaller-labse - Applying "Load What You Need: Smaller Versions of Multilingual BERT" to LaBSE
gensim - Topic Modelling for Humans
adaptnlp - An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
shap - A game theoretic approach to explain the output of any machine learning model. [Moved to: https://github.com/shap/shap]
Vision-DiffMask - Official PyTorch implementation of Vision DiffMask, a post-hoc interpretation method for vision models.