sentence-transformers
by UKPLab
State-of-the-Art Text Embeddings
AI summary
Text embeddings library
Provides dense vector representations for text using transformer networks
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huggingface/transformers136.4K
Model repository
A collection of pre-trained machine learning models for various natural language and computer vision tasks, enabling developers to fine-tune and deploy these models on their own projects.
Language model backend
Implementations of a neural network architecture for language modeling
Embedding models
Code for training universal paraphrastic sentence embeddings and models on semantic similarity tasks
BERT model
An implementation of Google's 2018 BERT model in PyTorch, allowing pre-training and fine-tuning for natural language processing tasks
Topic analyzer
This tool allows developers to extract and analyze topics from large text datasets using transformer-based models and topic modeling techniques.
Inference engine
A high-performance inference engine for transformer models
Segmentation Model Library
A comprehensive library for training and applying deep learning models for image segmentation
Transformer library
Provides tools and libraries for training and fine-tuning large language models using transformer architectures
Sentence embeddings library
Reproducible research on cross-lingual sentence embeddings using power mean word embeddings
GPU tensor library
A Python library providing tensors and dynamic neural networks with strong GPU acceleration
Transfer learning library
A unified library for parameter-efficient and modular transfer learning in NLP tasks
Sequence translator
An implementation of the Transformer model in PyTorch, a deep learning framework for sequence-to-sequence tasks like language translation.
Transformer library
An implementation of transformer models in PyTorch for natural language processing tasks
Sentence Embedder
Provides training and testing code for a CNN-based sentence embedding model
NLP tutorial
A comprehensive guide to using the Transformers library for natural language processing tasks
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