Instructions to use JayNightmare/PrERT-CNM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JayNightmare/PrERT-CNM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JayNightmare/PrERT-CNM")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JayNightmare/PrERT-CNM") model = AutoModelForSequenceClassification.from_pretrained("JayNightmare/PrERT-CNM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "generated_at": "2026-07-01T03:54:45.756651+00:00", | |
| "model_id": "JayNightmare/PrERT-CNM-v4-privacybert", | |
| "checkpoint": "D:\\Documents\\Personal-Projects\\PrERT-CNM-v4\\artifacts\\phase-3-privacybert\\classifier_checkpoint\\privacybert", | |
| "model_output": "D:\\Documents\\Personal-Projects\\PrERT-CNM-v4\\dist\\huggingface\\model", | |
| "space_output": "D:\\Documents\\Personal-Projects\\PrERT-CNM-v4\\dist\\huggingface\\space", | |
| "copied_model_files": [ | |
| "config.json", | |
| "model.safetensors", | |
| "tokenizer.json", | |
| "tokenizer_config.json", | |
| "training_metadata.json" | |
| ], | |
| "warnings": [] | |
| } |