Text Classification
Transformers
Safetensors
Portuguese
English
bert
aes
Eval Results (legacy)
text-embeddings-inference
Instructions to use kamel-usp/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kamel-usp/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kamel-usp/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kamel-usp/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only") model = AutoModelForSequenceClassification.from_pretrained("kamel-usp/jbcs2025_BERTugues-base-portuguese-cased-encoder_classification-C1-essay_only", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e14712fd80823f739ef235ace7329eefc74f99e49d9132cb8a03f7fba7789fa2
- Size of remote file:
- 438 MB
- SHA256:
- 64259312cfc1470926a6fc2d19809fe7f3812d38cf2fa96690278d9bb26ff5ae
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