Feature Extraction
Transformers
Safetensors
bert
mental-health
multi-label
mental-bert-base-uncased
text-embeddings-inference
Instructions to use mahir2021/mental-bert-depemo2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mahir2021/mental-bert-depemo2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="mahir2021/mental-bert-depemo2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("mahir2021/mental-bert-depemo2") model = AutoModel.from_pretrained("mahir2021/mental-bert-depemo2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download per_label_report.csv from mahir2021/mental-bert-depemo2: direct link, hf CLI and curl.
- Browser
- Download file 616 Bytes
-
https://huggingface.co/mahir2021/mental-bert-depemo2/resolve/main/per_label_report.csv
- Command line
-
hf download hf://mahir2021/mental-bert-depemo2/per_label_report.csv
-
curl -L -o per_label_report.csv https://huggingface.co/mahir2021/mental-bert-depemo2/resolve/main/per_label_report.csv
616 Bytes
| label,precision,recall,f1-score,support | |
| anger,0.6856581532416502,0.8880407124681934,0.7738359201773836,393 | |
| brain dysfunction (forget),0.432,0.6390532544378699,0.5155131264916468,169 | |
| emptiness,0.7576601671309192,0.8023598820058997,0.7793696275071633,339 | |
| hopelessness,0.8227334235453315,0.9514866979655712,0.8824383164005806,639 | |
| loneliness,0.8253968253968254,0.8524590163934426,0.8387096774193549,427 | |
| sadness,0.83270911360799,0.9638728323699421,0.8935030140656397,692 | |
| suicide intent,0.7644787644787645,0.853448275862069,0.8065173116089613,232 | |
| worthlessness,0.7142857142857143,0.9251101321585903,0.8061420345489443,454 | |