Text Classification
Transformers
TensorBoard
Safetensors
bert
Trained with AutoTrain
text-embeddings-inference
Instructions to use institutional/institutional-books-topic-classifier-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use institutional/institutional-books-topic-classifier-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="institutional/institutional-books-topic-classifier-bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("institutional/institutional-books-topic-classifier-bert") model = AutoModelForSequenceClassification.from_pretrained("institutional/institutional-books-topic-classifier-bert") - Notebooks
- Google Colab
- Kaggle
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Complete experimental setup and results are available in our [technical report](https://arxiv.org/abs/2506.08300) (Section 4.5).
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Code: https://github.com/instdin/institutional-books-1-pipeline
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## Base model
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[google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased)
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Complete experimental setup and results are available in our [technical report](https://arxiv.org/abs/2506.08300) (Section 4.5).
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**Code:** https://github.com/instdin/institutional-books-1-pipeline
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## Base model
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[google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased)
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