Instructions to use debjyoti007/new_doc_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use debjyoti007/new_doc_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="debjyoti007/new_doc_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("debjyoti007/new_doc_classifier") model = AutoModelForSequenceClassification.from_pretrained("debjyoti007/new_doc_classifier") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
This model has been trained for the purpose of classifying text from different domains. Currently it is trained with much lesser data and it has been trained to identify text from 3 domains, "sports", "healthcare" and "financial". Label_0 represents "financial", Label_1 represents "Healthcare" and Label_2 represents "Sports". Currently I have trained it with these 3 domains only, I am pretty soon planning to train it on more domains and more data, hence its accuracy will improve further too.
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