Text Classification
Transformers
Safetensors
multi-head-deberta-for-sequence-classification
custom_code
Instructions to use wandb/WeaveToxicityScorerV1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wandb/WeaveToxicityScorerV1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wandb/WeaveToxicityScorerV1", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("wandb/WeaveToxicityScorerV1", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| from transformers import DebertaV2Config | |
| class MultiHeadDebertaV2Config(DebertaV2Config): | |
| model_type = "multi-head-deberta-for-sequence-classification" | |
| def __init__(self, num_heads=5, **kwargs): | |
| self.num_heads = num_heads | |
| super().__init__(**kwargs) |