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
14
Safetensors
Model size
70.8M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.