facebookresearch / cycle_gan_for_complementary_item_recommendationsLinks
Research code of Cycle Generative Adversarial Networks for Complementary Item Recommendations.
☆20Updated 2 years ago
Alternatives and similar repositories for cycle_gan_for_complementary_item_recommendations
Users that are interested in cycle_gan_for_complementary_item_recommendations are comparing it to the libraries listed below
Sorting:
- Implementation of TableFormer, Robust Transformer Modeling for Table-Text Encoding, in Pytorch☆39Updated 3 years ago
- Implementation of a Transformer using ReLA (Rectified Linear Attention) from https://arxiv.org/abs/2104.07012☆49Updated 3 years ago
- Implementation of the Kalman Filtering Attention proposed in "Kalman Filtering Attention for User Behavior Modeling in CTR Prediction"☆59Updated 2 years ago
- Code for COMET: Cardinality Constrained Mixture of Experts with Trees and Local Search☆11Updated 2 years ago
- [NeurIPS 2022] Your Transformer May Not be as Powerful as You Expect (official implementation)☆33Updated 2 years ago
- ☆37Updated 2 years ago
- [COLM 2024] Early Weight Averaging meets High Learning Rates for LLM Pre-training☆18Updated last year
- PyTorch Implementation of the paper "MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training"☆24Updated last week
- My explorations into editing the knowledge and memories of an attention network☆35Updated 2 years ago
- A python library for highly configurable transformers - easing model architecture search and experimentation.☆49Updated 3 years ago
- Implementation of the general framework for AMIE, from the paper "Towards Conversational Diagnostic AI", out of Google Deepmind☆68Updated last year
- ☆16Updated last year
- Implementation of Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer in PyTorch.☆52Updated 2 years ago
- Some personal experiments around routing tokens to different autoregressive attention, akin to mixture-of-experts☆119Updated last year
- This is the official PyTorch repo for "UNIREX: A Unified Learning Framework for Language Model Rationale Extraction" (ICML 2022).☆26Updated 2 years ago
- A dashboard for exploring timm learning rate schedulers☆19Updated last year
- Implementation of Infini-Transformer in Pytorch☆113Updated 10 months ago
- Explorations into adversarial losses on top of autoregressive loss for language modeling☆38Updated 9 months ago
- Minimum Description Length probing for neural network representations☆20Updated 9 months ago
- Implementation of Multistream Transformers in Pytorch☆54Updated 4 years ago
- Exploration into the Scaling Value Iteration Networks paper, from Schmidhuber's group☆37Updated last year
- Few-shot Learning with Auxiliary Data☆31Updated last year
- Repository for the paper Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning☆36Updated 2 years ago
- Code for the PAPA paper☆27Updated 3 years ago
- Benchmarks for Business Document Foundation Models☆10Updated last year
- ☆31Updated last year
- PyTorch implementation of Soft MoE by Google Brain in "From Sparse to Soft Mixtures of Experts" (https://arxiv.org/pdf/2308.00951.pdf)☆78Updated 2 years ago
- A regression-alike loss to improve numerical reasoning in language models - ICML 2025☆26Updated 3 months ago
- Virtual Adversarial Training (VAT) techniques in PyTorch☆17Updated 3 years ago
- Experimental scripts for researching data adaptive learning rate scheduling.☆22Updated 2 years ago