Text Classification
Transformers
Safetensors
Portuguese
English
bert
aes
Eval Results (legacy)
text-embeddings-inference
Instructions to use kamel-usp/jbcs2025_bert-large-portuguese-cased-encoder_classification-C4-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-large-portuguese-cased-encoder_classification-C4-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-large-portuguese-cased-encoder_classification-C4-essay_only")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kamel-usp/jbcs2025_bert-large-portuguese-cased-encoder_classification-C4-essay_only") model = AutoModelForSequenceClassification.from_pretrained("kamel-usp/jbcs2025_bert-large-portuguese-cased-encoder_classification-C4-essay_only", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 882 Bytes
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2025-07-09T16:57:32,jbcs2025,7a85afea-dff9-4bbd-b1a0-463b436487b3,bert-large-portuguese-cased-encoder_classification-C4-essay_only,214.8115161480382,0.004540770745458322,2.1138395309909884e-05,48.38000000000001,168.23537292801586,58.0,0.002605466347188703,0.012872615853639857,0.003395947740847801,0.018874029941676355,Romania,ROU,gorj county,,,Linux-5.15.0-143-generic-x86_64-with-glibc2.35,3.12.11,3.0.2,36,Intel(R) Xeon(R) Gold 6248R CPU @ 3.00GHz,1,1 x NVIDIA RTX A6000,23.2904,45.0489,393.6063117980957,machine,N,1.0
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