Update README.md

README.md

@@ -1,3 +1,47 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- yaful/MAGE
+- liamdugan/raid
+language:
+- en
+base_model:
+- answerdotai/ModernBERT-base
+library_name: transformers
+pipeline_tag: text-classification
+---
+
+# Machine-generated text detection prevents language model collapse
+
+This model is part of the research presented in the paper [Machine-generated text detection prevents language model collapse](https://arxiv.org/abs/2502.15654), which proposes an approach to prevent model collapse based on importance sampling from a machine-generated text detector. The official implementation and training scripts are available in the GitHub repository: [GeorgeDrayson/model_collapse](https://github.com/GeorgeDrayson/model_collapse)
+
+## Usage
+
+To use the model for detecting machine-generated text:
+
+```python
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+tokenizer = AutoTokenizer.from_pretrained("GeorgeDrayson/modernbert-raid-mage")
+model = AutoModelForSequenceClassification.from_pretrained("GeorgeDrayson/modernbert-raid-mage")
+
+text = "Your input text here."
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model(**inputs)
+probabilities = torch.nn.functional.softmax(outputs.logits, dim=-1)
+print(f"Probability of machine-generated text: {probabilities[0][1].item():.4f}")
+```
+
+## Citation
+
+If you use this model or find the research helpful, please cite:
+
+```bibtex
+@article{drayson2025machine,
+  title={Machine-generated text detection prevents language model collapse},
+  author={Drayson, George and Yilmaz, Emine and Lampos, Vasileios},
+  journal={arXiv preprint arXiv:2502.15654},
+  year={2025}
+}
+```