GitHub - facebookresearch/d2go: D2Go is a toolkit for efficient deep learningYou signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session. Dismiss alert
GitHub - facebookresearch/fairseq: Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers: List of implemented papers Convolutional Neural Networks (CNN) Language Modeling with Gated Convolutional Networks (Dauphin et al., 2017)
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GitHub - facebookresearch/dlrm: An implementation of a deep learning recommendation model (DLRM)
GitHub - facebookresearch/StarSpace: Learning embeddings for classification, retrieval and ranking.
GitHub - facebookresearch/randsent: Exploring Random Encoders for Sentence Classification
GitHub - facebookresearch/InferSent: InferSent sentence embeddings
GitHub - facebookresearch/poincare-embeddings: PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"
GitHub - facebookresearch/DrQA: Reading Wikipedia to Answer Open-Domain Questions
GitHub - facebookresearch/darkforestGo: DarkForest, the Facebook Go engine.