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Roformer Chinese Small

Developed by junnyu
RoFormer is a Transformer model enhanced by Rotary Position Embedding (RoPE), suitable for Chinese text processing tasks.
Downloads 599
Release Time : 3/2/2022

Model Overview

This model employs Rotary Position Embedding (RoPE) technology to improve the traditional Transformer architecture, specifically optimized for Chinese text processing, supporting tasks like masked language modeling.

Model Features

Rotary Position Embedding (RoPE)
Utilizes innovative rotary position encoding technology, which captures sequence position information more effectively compared to traditional position encoding.
Chinese Optimization
Specifically optimized for Chinese text processing.
Multi-framework Support
Provides implementations for both PyTorch and TensorFlow 2.0.

Model Capabilities

Chinese Text Understanding
Masked Language Prediction
Contextual Semantic Analysis

Use Cases

Text Completion
Sentence Completion
Predicts masked words in sentences.
Examples show accurate predictions of words like 'weather' and 'want'.
Language Model Fine-tuning
Downstream Task Adaptation
Can be used as a pre-trained model for various Chinese NLP tasks.
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