Text Classification
Transformers
Safetensors
PyTorch
bert
hate-speech-detection
privhsd
glimo
text-embeddings-inference
Instructions to use batinium/glimo-dehatebert-hsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use batinium/glimo-dehatebert-hsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="batinium/glimo-dehatebert-hsd")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("batinium/glimo-dehatebert-hsd") model = AutoModelForSequenceClassification.from_pretrained("batinium/glimo-dehatebert-hsd") - Notebooks
- Google Colab
- Kaggle
| { | |
| "default_threshold": 0.850469, | |
| "id2label": { | |
| "0": "non_hate", | |
| "1": "hate" | |
| }, | |
| "label2id": { | |
| "hate": 1, | |
| "non_hate": 0 | |
| } | |
| } | |