Topic Modelling for Humans
- gensim
- topic-modeling
- information-retrieval
- machine-learning
Repository Index
47,133 repositories indexed
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A very simple framework for state-of-the-art Natural Language Processing (NLP)
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
- python
- search
- nlp
- semantic-search
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
- bert
- sentence-encoding
- deep-learning
- clip-model
Translated100+ Chinese Word Vectors
- chinese
- chinese-word-segmentation
- embeddings
- word-embeddings
Fast vectorization, topic modeling, distances and GloVe word embeddings in R.
- word2vec
- text-mining
- natural-language-processing
- glove
repository for Publicly Available Clinical BERT Embeddings
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
Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.
- artificial-intelligence
- clip
- pathology
- vision-and-language
BulkFormer: A large-scale foundation model for human bulk transcriptomes
CancerFoundation: A single-cell RNA sequencing foundation model to decipher drug resistance in cancer
- cancer
- foundation-model
- single-cell