Update README.md

README.md

@@ -1,3 +1,38 @@
----
-license: mit
----
+---
+license: mit
+language:
+- cs
+- en
+- es
+- fr
+- hi
+- pt
+base_model:
+- cardiffnlp/twitter-xlm-roberta-large-2022
+pipeline_tag: text-classification
+---
+# Model Overview
+
+This model is for stance classification on source-reply tweet pairs from Twitter/X. 
+It was fine-tuned on the training split of RumourEval2019 alongside synthetic tweets generated by [deepseek-ai/DeepSeek-R1-Distill-Qwen-14B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-14B)
+The starting point for fine-tuning was [cardiffnlp/twitter-xlm-roberta-large-2022](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-large-2022).
+
+## Synthetic Tweet Data
+
+The synthetic data was generated in Czech, English, Spanish, French, Hindi, and Portuguese.
+
+## Usage
+
+```python
+model_path = "GateNLP/stance-twitter-xlm-multilingual"
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+    model = AutoModelForSequenceClassification.from_pretrained(model_path, num_labels=4)
+
+source_tweet = "The Golden State Fence Company, hired to build part of the US-Mexico border wall, was fined $5 million for hiring illegal immigrant workers."
+reply_tweet = "@USER When did this happen?"
+inputs = tokenizer(text=tweet, text_pair=reply_tweet, return_tensors="pt")
+outputs = model(**inputs)
+
+labels = ["support", "deny", "query", "comment"]
+prediction = labels[outputs.logits.argmax()]
+```