Update README.md

README.md

@@ -1,4 +1,37 @@
 ---
+tags:
+  - text-classification
+  - emotion
+  - multi-label
+  - transformers
+  - deberta-v3
+  - huggingface
 widget:
-  - text: "I am feeling a little blue and anxious today..."
+  - text: "I feel excited but kind of anxious too."
 ---
+
+# DeBERTa V3 - Multi-label Emotion Classifier
+
+This model is a fine-tuned version of `microsoft/deberta-v3-base` for **multi-label emotion classification**.
+
+## Model Details
+
+- Base model: `DeBERTa V3`
+- Task: Multi-label emotion detection
+- Architecture: `DebertaV2ForSequenceClassification`
+- Number of labels: 14
+- Format: `safetensors`
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+tokenizer = AutoTokenizer.from_pretrained("PuroFuro/deberta-v3-emotion-multilabel")
+model = AutoModelForSequenceClassification.from_pretrained("PuroFuro/deberta-v3-emotion-multilabel")
+
+inputs = tokenizer("I feel nervous but hopeful.", return_tensors="pt")
+outputs = model(**inputs)
+probs = torch.sigmoid(outputs.logits)
+print(probs)