Update README.md

README.md

@@ -1,3 +1,53 @@
----
-license: mit
----
+---
+license: mit
+datasets:
+- artem9k/ai-text-detection-pile
+base_model:
+- FacebookAI/roberta-base
+---
+---
+language:
+- en
+pipeline_tag: text-classification
+tags:
+- ai-detection
+- roberta
+- generated-text-detection
+license: mit
+widget:
+  - text: "Machine learning is a subset of artificial intelligence."
+    example_title: "AI Example"
+  - text: "I went to the park to walk my dog yesterday."
+    example_title: "Human Example"
+---
+
+# My AI Text Detector (RoBERTa Base)
+
+This model is a fine-tuned version of `roberta-base` trained to distinguish between human-written text and AI-generated text.
+
+## Model Details
+- **Developer:** ShivamVN
+- **Base Model:** RoBERTa-base
+- **License:** MIT
+- **Finetuned on:** 80,000 samples from the `artem9k/ai-text-detection-pile` dataset.
+
+## How to Use
+
+You can use this model directly with the Hugging Face `transformers` library:
+
+```python
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+import torch
+
+model_name = "ShivamVN/My-Ai-Text-Detector"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+text = "Artificial Intelligence is changing the world."
+inputs = tokenizer(text, return_tensors="pt")
+
+with torch.no_grad():
+    logits = model(**inputs).logits
+
+probabilities = torch.softmax(logits, dim=1)
+print(f"AI Probability: {probabilities[0][1].item():.2f}")