# Text feature extraction

Amber Base is a Japanese-English sentence encoder model based on modernbert-ja-130m, specializing in sentence similarity calculation and feature extraction tasks.

This is a model trained based on sentence-transformers, capable of mapping sentences and paragraphs into a 768-dimensional dense vector space, suitable for various tasks such as semantic text similarity calculation and semantic search.

Snowflake Arctic Embed M v1.5 is an efficient sentence embedding model, focusing on sentence similarity calculation and feature extraction tasks.

bge_micro is a sentence embedding model based on sentence-transformers, focusing on sentence similarity calculation and feature extraction tasks.

This is a Polish sentence transformer model based on the KartonBERTa architecture, primarily used for sentence similarity calculation and feature extraction tasks.

bge_micro is a lightweight model focused on sentence similarity calculation, suitable for various natural language processing tasks.

bge_micro is a lightweight sentence similarity calculation model based on transformer architecture, specifically designed for efficient feature extraction and sentence similarity tasks.

This is an unsupervised SimCSE-based Japanese sentence embedding model, specifically designed for generating high-quality Japanese sentence embeddings.

Model fine-tuned on distilbert-base-uncased using the becasv2 dataset, with a validation loss of 5.9506

A Transformer model pre-trained on English corpus using ELECTRA-like objective functions, learning intrinsic representations of English language through self-supervised methods.

A BERT-based fine-tuned model for data skills, suitable for specific NLP tasks

Funnel Transformer is an English text pre-training model based on self-supervised learning, adopting objectives similar to ELECTRA, achieving efficient language processing by filtering sequence redundancy.

Transformer model pre-trained on English corpus using ELECTRA-like objectives, acquiring text representations through self-supervised learning

A Chinese ALBERT model pre-trained on CLUECorpusSmall, trained by the UER-py framework, suitable for Chinese text processing tasks.

Transformer model pre-trained on English corpus using ELECTRA-like objectives, suitable for text feature extraction and downstream task fine-tuning

GPT2-large Spanish language model trained on data from the National Library of Spain (BNE)