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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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model_name = "VictorYeste/deberta-based-human-value-detection"
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tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)
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model = transformers.AutoModelForSequenceClassification.from_pretrained(model_name)
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# Performance
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model_name = "VictorYeste/deberta-based-human-value-detection"
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tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)
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model = transformers.AutoModelForSequenceClassification.from_pretrained(model_name)
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```
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# Performance
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