Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Trong-Nghia/roberta-large-depression-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Trong-Nghia/roberta-large-depression-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Trong-Nghia/roberta-large-depression-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Trong-Nghia/roberta-large-depression-classification") model = AutoModelForSequenceClassification.from_pretrained("Trong-Nghia/roberta-large-depression-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1ea0c398471cd723d776bb63f40504b79f998fed517f1180aefba47cf1de9634
- Size of remote file:
- 1.42 GB
- SHA256:
- 930a1f00a15ca1f95c07dece1e92cd6ade049f857ab416b676047289091e0c46
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