Instructions to use viv/AIKIA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use viv/AIKIA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="viv/AIKIA")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("viv/AIKIA") model = AutoModelForSequenceClassification.from_pretrained("viv/AIKIA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# Offensive Language Detection Model for Modern Greek
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This model is fine-tuned to detect offensive language in Greek texts.
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## Model Details
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- Pretrained on `nlpaueb/bert-base-greek-uncased-v1`
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# Offensive Language Detection Model for Modern Greek
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This model is fine-tuned to detect offensive language in Greek texts (Twitter & Fiction).
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## Model Details
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- Pretrained on `nlpaueb/bert-base-greek-uncased-v1`
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