Text Classification
Transformers
Safetensors
English
distilbert
psychology
abuse-detection
darvo
manipulation-detection
mental-health
relationship-analysis
tether-pro
Eval Results (legacy)
text-embeddings-inference
Instructions to use SamanthaStorm/tether-darvo-regressor-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamanthaStorm/tether-darvo-regressor-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SamanthaStorm/tether-darvo-regressor-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SamanthaStorm/tether-darvo-regressor-v1") model = AutoModelForSequenceClassification.from_pretrained("SamanthaStorm/tether-darvo-regressor-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_type": "regression", | |
| "task": "darvo-detection", | |
| "version": "2.0", | |
| "performance": { | |
| "mse": 0.043, | |
| "mae": 0.171, | |
| "accuracy": 0.842, | |
| "auc": 0.881, | |
| "r_squared": 0.665 | |
| }, | |
| "training_examples": 285, | |
| "architecture": "distilbert-base-uncased + custom regression head" | |
| } |