CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
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Topic Modelling for Humans
- gensim
- topic-modeling
- information-retrieval
- machine-learning
A very simple framework for state-of-the-art Natural Language Processing (NLP)
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
- bert
- sentence-encoding
- deep-learning
- clip-model
Postgres with GPUs for ML/AI apps.
- ml
- machine-learning
- ai
- ann
Train and evaluate embeddings for similarity search with PyTorch. Includes contrastive losses, hard example mining, samplers, and retrieval metrics.
- metric-learning
- deep-learning
- computer-vision
- machine-learning
Chinese version of CLIP which achieves Chinese cross-modal retrieval and representation generation.
- chinese
- computer-vision
- multi-modal-learning
- nlp
PyTorch code and models for V-JEPA self-supervised learning from video.
Representation learning on large graphs using stochastic graph convolutions.
[EMNLP 2021] SimCSE: Simple Contrastive Learning of Sentence Embeddings https://arxiv.org/abs/2104.08821
- nlp
- sentence-embeddings
Open-source inference server and production cluster for all the models your agent needs.
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
- machine-learning
- convolutional-networks
- embedding-vectors
- embeddings
A python package to analyze and compare voices with deep learning
Siamese and triplet networks with online pair/triplet mining in PyTorch
- machine-learning
- deep-learning
- siamese-network
- triplet-loss
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
- community-detection
- graph-clustering
- deepwalk
- networkx
🚀 Catalyst is a C# Natural Language Processing library built for speed. Inspired by spaCy's design, it brings pre-trained models, out-of-the box support for training word and document embeddings, and flexible entity recognition models.
Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
- deep-learning
- protein-sequences
- protein-structure
- semi-supervised-learning
A simple deep learning library for estimating a set of tags and extracting semantic feature vectors from given illustrations.
Cleora AI is a general-purpose open-source model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data. Created by Synerise.com team.
- ai
- graphs
- synerise
- embeddings
Learning Heterogeneous Tactile Representation for General Dexterous Manipulation
This is a german ELMo deep contextualized word representation. It is trained on a special German Wikipedia Text Corpus.
- bilm
- elmo
- tensorflow
- machine-learning
gtfs2vec - Learning GTFS Embeddings for comparing PublicTransport Offer in Microregions