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Data2vec Nlp Base
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Data2vec Nlp Base
Developed by edugp
Data2Vec NLP Base is a natural language processing model converted from the fairseq framework, suitable for tasks such as text classification.
Downloads 14
Release Time : 3/2/2022
Model Overview
This model is a basic NLP model converted from the fairseq framework, primarily used for sequence classification tasks.
Model Features
Based on Data2Vec Architecture
Utilizes the Data2Vec self-supervised learning framework to learn general text representations.
Easy to Fine-tune
Designed for easy fine-tuning on downstream tasks.
Compatible with RoBERTa
Uses RoBERTa tokenizer and is compatible with existing NLP toolchains.
Model Capabilities
Text Classification
Sequence Labeling
Natural Language Understanding
Use Cases
Text Analysis
Sentiment Analysis
Analyze the sentiment tendency in text.
Topic Classification
Classify text into predefined topic categories.
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