Text Classification
Transformers
Safetensors
Spanish
bert
hate-speech
toxicity
spanish
el-salvador
mbert
Eval Results (legacy)
text-embeddings-inference
Instructions to use caeher/mbert-sv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caeher/mbert-sv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="caeher/mbert-sv")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("caeher/mbert-sv") model = AutoModelForSequenceClassification.from_pretrained("caeher/mbert-sv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Actualizar modelo entrenado (epoch 5, F1-macro val 0.775)
Verified signatureEntrenamiento con optimizacion F1 en validacion. Metricas: eval_f1_macro=0.775, eval_accuracy=0.776, eval_loss=1.042.f0fb366
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Add mBERT-SV checkpoint-1072 (F1-macro 0.7777)
Verified signature2ea985e -
initial commit
Verified signature3f9014e