# Dependency Parsing

General-purpose natural language processing pipeline for Ancient Greek, supporting multiple tasks including POS tagging and dependency parsing

Medium-sized spaCy pipeline optimized for Turkish, including tokenization, part-of-speech tagging, morphological analysis, dependency parsing, and named entity recognition

DeBERTa(V2) model pretrained on Japanese Wikipedia and Aozora Bunko texts, suitable for Japanese text processing tasks

CPU-optimized Finnish language processing pipeline with NLP features including token classification and dependency parsing

CPU-optimized Korean processing pipeline with complete NLP functions including tokenization, part-of-speech tagging, dependency parsing, named entity recognition, etc.

Korean processing pipeline optimized for CPU, including tokenization, part-of-speech tagging, dependency parsing, named entity recognition, etc.

Swedish small natural language processing model provided by spaCy, optimized for CPU, including complete NLP pipeline such as tokenization, part-of-speech tagging, and dependency parsing

A multilingual model for Maltese pre-trained on the Maltese corpus v4.0 based on multilingual BERT initial checkpoints

BERTu is a monolingual Maltese model based on the BERT architecture, specifically designed for low-resource languages, supporting various natural language processing tasks.

BERT model pre-trained on UD_German-HDT for German POS tagging and dependency parsing

spaCy's medium-sized English processing pipeline, optimized for CPU, including POS tagging, dependency parsing, named entity recognition, etc.

CPU-optimized Italian processing pipeline provided by spaCy, including NLP functionalities such as token classification, dependency parsing, and named entity recognition

CPU-optimized Romanian natural language processing model, including tokenization, part-of-speech tagging, dependency parsing, named entity recognition, and other functions

CPU-optimized Norwegian Bokmål processing pipeline, including token classification, dependency parsing, named entity recognition, etc.

CPU-optimized Lithuanian processing pipeline with complete NLP functions including tokenization, POS tagging, dependency parsing, and named entity recognition

Japanese processing pipeline optimized for CPU, including tokenization, part-of-speech tagging, dependency parsing, named entity recognition, etc.

A CPU-optimized small English language processing pipeline provided by spaCy, including core functionalities such as tokenization, part-of-speech tagging, dependency parsing, and named entity recognition

A CPU-optimized small French natural language processing model provided by spaCy, featuring tokenization, part-of-speech tagging, dependency parsing, named entity recognition, and more.

A medium-sized Spanish NLP processing pipeline provided by spaCy, optimized for CPU usage, containing complete language processing components

A Transformer-based English NLP pipeline model providing high-performance named entity recognition, part-of-speech tagging, and dependency parsing.

spaCy's CPU-optimized Portuguese processing pipeline, including tokenization, POS tagging, dependency parsing, named entity recognition, etc.

CPU-optimized German processing pipeline including tokenization, part-of-speech tagging, morphological analysis, dependency parsing, lemmatization, named entity recognition, etc.

Large German language processing model provided by spaCy, supporting NLP tasks such as POS tagging, dependency parsing, and named entity recognition

CPU-optimized Russian processing pipeline including token classification, dependency parsing, named entity recognition and other NLP tasks

A CPU-optimized Spanish natural language processing pipeline, including tokenization, part-of-speech tagging, dependency parsing, named entity recognition, and more.

Chinese processing pipeline optimized for CPU, including tokenization, part-of-speech tagging, dependency parsing, named entity recognition, etc.

Chinese natural language processing pipeline based on Transformer, including part-of-speech tagging, dependency parsing, named entity recognition, etc.

CPU-optimized Chinese natural language processing pipeline, including tokenization, part-of-speech tagging, dependency parsing, named entity recognition, and more

CPU-optimized Romanian language processing pipeline with complete NLP components including token classification, dependency parsing, and named entity recognition

CPU-optimized Dutch processing pipeline including tokenization, POS tagging, dependency parsing, named entity recognition, etc.

Large English language processing model provided by spaCy, optimized for CPU, featuring a complete natural language processing pipeline

CPU-optimized Dutch processing pipeline containing NLP task components such as tokenization, part-of-speech tagging, dependency parsing, and named entity recognition

A RoBERTa model pretrained on Aozora Bunko texts using a character tokenizer, suitable for Japanese text processing tasks.

Japanese RoBERTa model pre-trained on Aozora Bunko texts, supporting masked language modeling tasks

RoBERTa large Japanese model pretrained on Aozora Bunko texts, supports downstream task fine-tuning

This is a model based on the RoBERTa pre-trained model, using the UD_English dataset for POS tagging and dependency parsing.