Text Classification
Transformers
PyTorch
Safetensors
Portuguese
Trained with AutoTrain
Eval Results (legacy)
Instructions to use inctdd/told_br_binary_sm_bertimbau with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inctdd/told_br_binary_sm_bertimbau with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="inctdd/told_br_binary_sm_bertimbau")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("inctdd/told_br_binary_sm_bertimbau", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
a30264b
1
Parent(s): ad83af3
Update README.md
Browse files
README.md
CHANGED
|
@@ -32,7 +32,7 @@ co2_eq_emissions:
|
|
| 32 |
|
| 33 |
## Usage
|
| 34 |
|
| 35 |
-
This model was trained on a random subset of the [
|
| 36 |
model that can be used to classify Brazilian Portuguese tweets in a binary way ('toxic' or 'non toxic').
|
| 37 |
|
| 38 |
You can use cURL to access this model:
|
|
|
|
| 32 |
|
| 33 |
## Usage
|
| 34 |
|
| 35 |
+
This model was trained on a random subset of the [told-br](https://huggingface.co/datasets/told-br) dataset (1/3 of the original size). Our main objective is to provide a small
|
| 36 |
model that can be used to classify Brazilian Portuguese tweets in a binary way ('toxic' or 'non toxic').
|
| 37 |
|
| 38 |
You can use cURL to access this model:
|