Edit model card

Malay-Language Sentiment Classification

Overview

This model is a fine-tuned checkpoint of Deberta-V3-xsmall. It enables binary sentiment analysis for Malay-language text. For each instance, it predicts either positive (1) or negative (0) sentiment. Model is trained on all data from https://github.com/mesolitica/malaysian-dataset/tree/master/sentiment.

Use in a Hugging Face pipeline

The easiest way to use the model for single predictions is Hugging Face's sentiment analysis pipeline, which only needs a couple lines of code as shown in the following example:

from transformers import pipeline
sentiment_analysis = pipeline("sentiment-analysis",model="malaysia-ai/deberta-v3-xsmall-malay-sentiment")
print(sentiment_analysis("saya comel"))
Downloads last month
5
Safetensors
Model size
70.8M params
Tensor type
F32
·