Text Classification
Transformers
TensorFlow
bert
generated_from_keras_callback
text-embeddings-inference
Instructions to use thiagoads/modelo-de-exemplo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thiagoads/modelo-de-exemplo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thiagoads/modelo-de-exemplo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thiagoads/modelo-de-exemplo") model = AutoModelForSequenceClassification.from_pretrained("thiagoads/modelo-de-exemplo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
modelo-de-exemplo
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on an unknown dataset. It achieves the following results on the evaluation set:
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- optimizer: None
- training_precision: float32
Training results
Framework versions
- Transformers 4.33.1
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.13.3
- Downloads last month
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Model tree for thiagoads/modelo-de-exemplo
Base model
neuralmind/bert-base-portuguese-cased