Instructions to use devnote5676/schwartz-values-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devnote5676/schwartz-values-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="devnote5676/schwartz-values-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("devnote5676/schwartz-values-classifier") model = AutoModelForSequenceClassification.from_pretrained("devnote5676/schwartz-values-classifier") - Notebooks
- Google Colab
- Kaggle
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README.md
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## How to use
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Start your sentence with a label that indicates which dimension to measure. An example would be:
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- <power> [SEP] staying out late after telling my girlfriend I could be home early
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Please make sure to follow the exact format "<value\_name>" at the beginning of the sentence as this is a special token in the tokenizer: any spaces or different formats will not be encoded correctly.
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## How to use
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Start your sentence with a label that indicates which dimension to measure. An example would be:
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- \<power> [SEP] staying out late after telling my girlfriend I could be home early
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Please make sure to follow the exact format "<value\_name>" at the beginning of the sentence as this is a special token in the tokenizer: any spaces or different formats will not be encoded correctly.
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