Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Trong-Nghia/roberta-large-detect-dep-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Trong-Nghia/roberta-large-detect-dep-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Trong-Nghia/roberta-large-detect-dep-v3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Trong-Nghia/roberta-large-detect-dep-v3") model = AutoModelForSequenceClassification.from_pretrained("Trong-Nghia/roberta-large-detect-dep-v3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66519c04b387c03e6bc600c88354920489a235aa3909c9c6e116a156a055434e
- Size of remote file:
- 1.42 GB
- SHA256:
- 2efd370c4748f7ec2ba8027f36a4b5381c1603784fe0dc8728e86d95675a305a
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