Instructions to use kamel-usp/aes_enem_models-sourceB-ordinal-large-C2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kamel-usp/aes_enem_models-sourceB-ordinal-large-C2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kamel-usp/aes_enem_models-sourceB-ordinal-large-C2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kamel-usp/aes_enem_models-sourceB-ordinal-large-C2") model = AutoModelForSequenceClassification.from_pretrained("kamel-usp/aes_enem_models-sourceB-ordinal-large-C2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a270ca5da140af295330c06cb76bd01d5489a22e9e69fb53b16f64a2f5e1424f
- Size of remote file:
- 1.34 GB
- SHA256:
- 99d280928d4ba1f3a5dc143c81fb2e68ba6093b3648c3461f3f522f7c4579a4d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.