Create README.md

README.md

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+---
+language:
+- ms
+---
+
+## SiEBERT - Malay-Language Sentiment Classification
+
+# Overview
+This model is a fine-tuned checkpoint of [Deberta-V3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall). It enables binary sentiment analysis for Malay-language text. For each instance, it predicts either positive (1) or negative (0) sentiment. 
+
+
+
+# Use in a Hugging Face pipeline
+The easiest way to use the model for single predictions is Hugging Face's [sentiment analysis pipeline](https://huggingface.co/transformers/quicktour.html#getting-started-on-a-task-with-a-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"))
+```
+
+
+