Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use ericNguyen0132/roberta-large-Dep-first with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ericNguyen0132/roberta-large-Dep-first with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ericNguyen0132/roberta-large-Dep-first")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ericNguyen0132/roberta-large-Dep-first") model = AutoModelForSequenceClassification.from_pretrained("ericNguyen0132/roberta-large-Dep-first") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e68f999f9aa5f1feb351355b766c8c8dcac827a3cd44544c93d62b79ded56f43
- Size of remote file:
- 4.03 kB
- SHA256:
- 3f61909545189f3486b2cb256df8ad03355e4414f5a421d3f04784ed7b7891f9
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