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:
- 6f0cb77c03ea321b3383225e4365b414e3270db9d6ad1e6fa12dd89570a7c6fd
- Size of remote file:
- 1.42 GB
- SHA256:
- 41ff9cfebbbe3e1c28c1c5a76426daefa9dc2b40626d5b37d47caf497c5573a3
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