Upload README.md

README.md

@@ -0,0 +1,43 @@
+---
+# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
+# Doc / guide: https://huggingface.co/docs/hub/model-cards
+license: mit
+language:
+- multilingual
+---
+# Model Card for xlm-roberta-large-binary-cs-iib
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This model is fine-tuned for text classification of Supportive Interactions in Instant Messenger dialogs of Adolescents. The classification is binary and the model outputs probablities for labels> 0,1: Supportive Interactions present or not.
+
+## Model Details
+
+### Model Description
+
+Fine-tuned on the machine-translated version of a dataset of Instant Messenger dialogs of Adolescents originally in the Czech language.
+
+- **Developed by:** Anonymous
+- **Language(s):** multi-lingual
+- **Finetuned from:** xlm-roberta-large
+
+### Model Sources
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** https://github.com/chi2024submission
+- **Paper:** Stay tuned!
+
+## Usage
+Here is how to use this model to classify a context-window of a dialogue:
+
+```python
+from transformers import AutoTokenizer, AutoModel
+tokenizer = AutoTokenizer.from_pretrained('xlm-roberta-large')
+model = AutoModelForSequenceClassification.from_pretrained("chi2024/xlm-roberta-large-binary-cs-iib")
+# prepare input
+utterances = "Hi, how are you?;I am fine, how about you?;Thanks for asking."
+encoded_input = tokenizer(text, return_tensors='pt')
+# forward pass
+output = model(**encoded_input)
+```