Text Classification
Transformers
Safetensors
deberta
human value detection
text classification
multi-label clasification
Instructions to use VictorYeste/deberta-based-human-value-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VictorYeste/deberta-based-human-value-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="VictorYeste/deberta-based-human-value-detection")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VictorYeste/deberta-based-human-value-detection") model = AutoModelForSequenceClassification.from_pretrained("VictorYeste/deberta-based-human-value-detection") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fea756210e6dab62292b06e7466ba484b9f4a52a00858056317519563739d34a
- Size of remote file:
- 557 MB
- SHA256:
- 8f3e3108124444a4765f1b84ad533aa6fe17110e26ad0a85e2d65ec9f04541ed
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