Topic Modelling for Humans
- gensim
- topic-modeling
- information-retrieval
- machine-learning
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Topic Modelling for Humans
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
🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP
Translated100+ Chinese Word Vectors
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.
A simple deep learning library for estimating a set of tags and extracting semantic feature vectors from given illustrations.
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.