Instructions to use software-si/change-language-intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use software-si/change-language-intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="software-si/change-language-intent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("software-si/change-language-intent") model = AutoModelForSequenceClassification.from_pretrained("software-si/change-language-intent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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## ๐ Training Data
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- ~6,000 training examples
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- Short conversational sentences (e.g. "Can we switch to English?", "Vorrei parlare in italiano", "Nein, bitte auf Deutsch")
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- Languages covered: English, Italian, German, Spanish, French
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- `not_allowed` and `other` provide robustness for real-world inputs
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- 2/3 conversation steps
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## ๐ Usage with ๐ค Transformers
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## ๐ Training Data
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- ~6,000 training examples
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- Short conversational sentences (e.g. "Can we switch to English?", "Vorrei parlare in italiano", "Nein, bitte auf Deutsch"), and pieaces of conversation steps
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- Languages covered: English, Italian, German, Spanish, French
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- `not_allowed` and `other` provide robustness for real-world inputs
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## ๐ Usage with ๐ค Transformers
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