Text Classification
Transformers
Safetensors
deberta
human value detection
text classification
multi-label clasification
Instructions to use VictorYeste/deberta-based-human-value-stance-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-stance-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-stance-detection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("VictorYeste/deberta-based-human-value-stance-detection") model = AutoModelForSequenceClassification.from_pretrained("VictorYeste/deberta-based-human-value-stance-detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from VictorYeste/deberta-based-human-value-stance-detection: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/VictorYeste/deberta-based-human-value-stance-detection/resolve/main/tokenizer.json
- Command line
-
hf download hf://VictorYeste/deberta-based-human-value-stance-detection/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/VictorYeste/deberta-based-human-value-stance-detection/resolve/main/tokenizer.json
2.11 MB
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