nlp-tutorial VS TokenCut

Compare nlp-tutorial vs TokenCut and see what are their differences.

TokenCut

(CVPR 2022) Pytorch implementation of "Self-supervised transformers for unsupervised object discovery using normalized cut" (by YangtaoWANG95)
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nlp-tutorial TokenCut
1 1
13,712 285
- -
0.0 1.2
2 months ago about 1 year ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
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nlp-tutorial

Posts with mentions or reviews of nlp-tutorial. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-29.

TokenCut

Posts with mentions or reviews of TokenCut. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing nlp-tutorial and TokenCut you can also consider the following projects:

nlp_course - YSDA course in Natural Language Processing

pytorch-GAT - My implementation of the original GAT paper (Veliฤkoviฤ‡ et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!

pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.

poolformer - PoolFormer: MetaFormer Is Actually What You Need for Vision (CVPR 2022 Oral)

awesome-nlp - :book: A curated list of resources dedicated to Natural Language Processing (NLP)

nn - ๐Ÿง‘โ€๐Ÿซ 60 Implementations/tutorials of deep learning papers with side-by-side notes ๐Ÿ“; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), ๐ŸŽฎ reinforcement learning (ppo, dqn), capsnet, distillation, ... ๐Ÿง 

nlp-recipes - Natural Language Processing Best Practices & Examples

D2L_Attention_Mechanisms_in_TF - This repository contains Tensorflow 2 code for Attention Mechanisms chapter of Dive into Deep Learning (D2L) book.

transformers - ๐Ÿค— Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

pytorch-seq2seq - Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

tf-transformers - State of the art faster Transformer with Tensorflow 2.0 ( NLP, Computer Vision, Audio ).

nlp-in-python-tutorial - comparing stand up comedians using natural language processing