transformers-interpret
PyTorch-NLP
transformers-interpret | PyTorch-NLP | |
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3 | 1 | |
1,212 | 2,180 | |
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2.9 | 0.0 | |
8 months ago | 10 months ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
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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
PyTorch-NLP
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Introduction to PyTorch
PyTorch-NLP
What are some alternatives?
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small-text - Active Learning for Text Classification in Python
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
happy-transformer - Happy Transformer makes it easy to fine-tune and perform inference with NLP Transformer models.
NLTK - NLTK Source
gensim - Topic Modelling for Humans
pytext - A natural language modeling framework based on PyTorch
Jieba - 结巴中文分词
shap - A game theoretic approach to explain the output of any machine learning model. [Moved to: https://github.com/shap/shap]
Stanza - Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages