Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+language:
+- th
+tags:
+- sequence-tagging
+- aspect-based-sentiment
+---
+
+# XLM-RoBERTa-Large for Aspect-Based Sentiment Analysis
+
+This is a fine-tuned XLM-RoBERTa-Large model for Aspect-Based Sentiment Analysis in Thai. The model is fine-tuned on a dataset specifically for the task of identifying sentiments related to specific aspects within sentences.
+
+## Model Description
+
+XLM-RoBERTa is a large multilingual language model that has been fine-tuned for sequence tagging tasks. This model has been further fine-tuned for Aspect-Based Sentiment Analysis, making it suitable for applications that require understanding of sentiments expressed towards specific aspects within a text.
+
+## Usage
+
+You can use this model for sequence tagging and aspect-based sentiment analysis in the Thai language. Here is a quick example of how to use it:
+
+```python
+from transformers import AutoTokenizer, AutoModelForTokenClassification
+from transformers import pipeline
+
+tokenizer = AutoTokenizer.from_pretrained("path_to_your_model")
+model = AutoModelForTokenClassification.from_pretrained("path_to_your_model")
+
+nlp = pipeline("token-classification", model=model, tokenizer=tokenizer)
+
+text = "ใส่ประโยคภาษาไทยที่ต้องการวิเคราะห์ที่นี่"
+result = nlp(text)
+
+for item in result:
+    print(item)
+