Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
text-embeddings-inference
Instructions to use reichenbach/deberta_toxic_cls with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use reichenbach/deberta_toxic_cls with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="reichenbach/deberta_toxic_cls")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("reichenbach/deberta_toxic_cls") model = AutoModelForSequenceClassification.from_pretrained("reichenbach/deberta_toxic_cls", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 133a91a116f86fba964f128a763868122a7048e5bd6f80fdce83bce0016ba088
- Size of remote file:
- 5.84 kB
- SHA256:
- 288663d4dae564292a49ddcd99d203282db760c60bcffd017f24a988a8d2a398
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