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:
- 0db2c63089e7a4fbe8883cb4bcd5c096b4d9926a9789f5a40aa0a373163440cc
- Size of remote file:
- 1.42 GB
- SHA256:
- c8f6b2b5e4a12cb3dfaa7f80f1f539b8f83acec64d2f6f7b4c1f2c228fa287b8
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