Instructions to use Joshfcooper/ai-text-detector-optimized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Joshfcooper/ai-text-detector-optimized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Joshfcooper/ai-text-detector-optimized")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Joshfcooper/ai-text-detector-optimized", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "ai_text_detector", | |
| "base_model": "HuggingFaceTB/SmolLM-135M", | |
| "architecture": "feature_extraction_classifier", | |
| "num_layers_used": 12, | |
| "total_layers": 30, | |
| "selected_layers": [ | |
| 0, | |
| 2, | |
| 4, | |
| 6, | |
| 8, | |
| 10, | |
| 12, | |
| 14, | |
| 16, | |
| 18, | |
| 20, | |
| 22 | |
| ], | |
| "feature_size": 13824, | |
| "sequence_length": 256, | |
| "compression_ratio": 0.6, | |
| "output_inverted": true, | |
| "task": "binary_classification", | |
| "labels": [ | |
| "ai", | |
| "human" | |
| ] | |
| } |