Text Classification
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aes
Eval Results (legacy)
text-embeddings-inference
Instructions to use kamel-usp/jbcs2025_bert-base-multilingual-cased-encoder_classification-C2-essay_only with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kamel-usp/jbcs2025_bert-base-multilingual-cased-encoder_classification-C2-essay_only with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kamel-usp/jbcs2025_bert-base-multilingual-cased-encoder_classification-C2-essay_only")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kamel-usp/jbcs2025_bert-base-multilingual-cased-encoder_classification-C2-essay_only") model = AutoModelForSequenceClassification.from_pretrained("kamel-usp/jbcs2025_bert-base-multilingual-cased-encoder_classification-C2-essay_only") - Notebooks
- Google Colab
- Kaggle
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