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Distilroberta Base V2
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Distilroberta Base V2

Developed by typeform
DistilRoBERTa is a lightweight distilled version of the RoBERTa model, retaining most of its performance with fewer parameters, making it suitable for efficient text processing tasks.
Large Language Model EnglishOpen Source License:Apache-2.0#Lightweight BERT#English Text Processing#Efficient Fine-tuning
Downloads 22
Release Time : 3/2/2022

Model Overview

This model is a distilled version of RoBERTa, reducing its size through knowledge distillation while maintaining strong natural language understanding capabilities, suitable for tasks like text classification and entity recognition.

Model Features

Lightweight and Efficient
Reduces parameters by 40% through knowledge distillation while retaining 97% of RoBERTa-base's performance
Fast Inference
Inference speed is approximately 60% faster compared to the original RoBERTa model
Versatility
Supports various downstream NLP tasks, including text classification, entity recognition, and question-answering systems

Model Capabilities

Text Understanding
Text Classification
Named Entity Recognition
Question-Answering Systems
Semantic Similarity Calculation

Use Cases

Text Analysis
Sentiment Analysis
Analyze sentiment tendencies in social media text
Accuracy can exceed 90% (estimated)
Content Classification
Automatically categorize news articles
Information Extraction
Entity Recognition
Extract entity information such as names and locations from text
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