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En Hi Pos Tagger Symcom
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En Hi Pos Tagger Symcom
Developed by prakod
XLM-RoBERTa-base is a multilingual pre-trained model based on the RoBERTa architecture, supporting multiple languages including Hindi and English.
Downloads 26
Release Time : 3/14/2022
Model Overview
This model is a multilingual pre-trained model suitable for natural language processing tasks such as token classification and POS tagging.
Model Features
Multilingual Support
Supports multiple languages, including Hindi and English, suitable for code-mixed text processing.
Pre-trained Model
Based on the RoBERTa architecture with strong language representation capabilities.
Token Classification
Suitable for token classification tasks such as POS tagging.
Model Capabilities
Multilingual Text Processing
Token Classification
POS Tagging
Use Cases
Natural Language Processing
Code-Mixed Text Analysis
Analyze code-mixed texts containing both English and Hindi.
High-accuracy POS tagging and token classification.
Multilingual POS Tagging
Perform POS tagging on multilingual texts.
Supports POS tagging tasks in multiple languages.
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