Instructions to use gsar78/HellenicSentimentAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsar78/HellenicSentimentAI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gsar78/HellenicSentimentAI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gsar78/HellenicSentimentAI") model = AutoModelForSequenceClassification.from_pretrained("gsar78/HellenicSentimentAI") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Model Details
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- **Model Name:** Hellenic Sentiment AI
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- **Model Version:** 1.
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- **Language:** Multilingual
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- **Framework:** Transformers
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- **Max Sequence Length:** 512
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- **Base Architecture:** roBERTa
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- **Training Data:** The model was trained on a custom, curated multilingual dataset, comprising human-handpicked reviews from products, places, and restaurants, with a specific emphasis on Greek language texts.
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## Production readiness
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## Model Details
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- **Model Name:** Hellenic Sentiment AI
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- **Model Version:** 1.1
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- **Language:** Greek only (Version 1.0), Multilingual (El, En, Fr, It, Es, De, Ar) (Version 1.1)
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- **Framework:** Transformers from HuggingFace
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- **Max Sequence Length:** 512
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- **Base Architecture:** roBERTa
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- **Training Data:** The model (version 1.1) was trained on a custom, curated multilingual dataset, comprising human-handpicked reviews from products, places, and restaurants, with a specific emphasis on Greek language texts.
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## Production readiness
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