Instructions to use gabrielhpr/enem-auto-correction-regression-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gabrielhpr/enem-auto-correction-regression-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gabrielhpr/enem-auto-correction-regression-1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gabrielhpr/enem-auto-correction-regression-1") model = AutoModelForSequenceClassification.from_pretrained("gabrielhpr/enem-auto-correction-regression-1") - Notebooks
- Google Colab
- Kaggle
enem-auto-correction-regression-1
This model was trained from scratch 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 4.31.0
- TensorFlow 2.13.0
- Datasets 2.14.4
- Tokenizers 0.13.3
- Downloads last month
- 9