Update README.md

README.md

@@ -1,3 +1,40 @@
----
-license: mit
----
+---
+language: en
+tags:
+- text-classification
+- pytorch
+- roberta
+- self-beliefs
+- multi-class-classification
+- multi-label-classification
+license: mit
+widget:
+- text: I am the coolest person I know.
+---
+
+#### Overview
+
+Model trained from [roberta-large](https://huggingface.co/roberta-large) on a dataset of human and LLM annotated self-beliefs for multi-label classification.
+
+### Training Details
+
+Model training , hyper-parameters, and evaluation  can be found in "Capturing Self-Beliefs in Natural Language" by Mangalik et al. 2024
+
+### Inference
+
+A sample way to use this model for classification
+
+```python
+from transformers import pipeline
+huggingface_model = 'sidmangalik/selfBERTa'
+model = RobertaForSequenceClassification.from_pretrained(huggingface_model)
+tokenizer = RobertaTokenizerFast.from_pretrained(huggingface_model, max_length = 512, padding="max_length", truncation=True)
+
+texts = ["I am the coolest person I know."]
+
+inputs = tokenizer(texts, max_length=512, padding="max_length", truncation=True, return_tensors='pt')
+outputs = model(**inputs)
+logits = outputs.logits
+soft_logits = torch.softmax(logits, dim=1).tolist()
+predicted_classes = np.argmax(soft_logits, axis=1)
+```