| license: apache-2.0 | |
| language: | |
| - en | |
| pipeline_tag: text-classification | |
| library_name: transformers | |
| tags: | |
| - text-classification | |
| - nlp | |
| - machine-learning | |
| - cyfuture-ai | |
| # Cyfuture AI Text Classifier | |
| Cyfuture AI Text Classifier is a lightweight natural language processing model designed for text classification and AI application prototyping. | |
| The model is intended as a practical reference for developers building AI applications that need to classify and organize text. | |
| ## Intended Use | |
| This model can be used for: | |
| - Text classification | |
| - Intent classification | |
| - Support ticket categorization | |
| - Document categorization | |
| - AI application prototyping | |
| - NLP experimentation | |
| ## Example Applications | |
| Potential applications include: | |
| - Automatically categorizing customer support requests | |
| - Classifying incoming business documents | |
| - Identifying user intents in conversational applications | |
| - Organizing text-based datasets | |
| - Building AI-powered workflow automation | |
| ## Usage | |
| After the model weights and tokenizer are uploaded, the model can be used with the Hugging Face Transformers library: | |
| ```python | |
| from transformers import pipeline | |
| classifier = pipeline( | |
| "text-classification", | |
| model="Cyfutureai/cyfuture-ai-text-classifier" | |
| ) | |
| result = classifier( | |
| "This is an example text for classification." | |
| ) | |
| print(result) |