Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use xshubhamx/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use xshubhamx/roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="xshubhamx/roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("xshubhamx/roberta-base") model = AutoModelForSequenceClassification.from_pretrained("xshubhamx/roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1274d350fd84da85a8edfbb0ab3419eca2a7abe0a6526a5c5fb24dc0d1492ec7
- Size of remote file:
- 997 MB
- SHA256:
- 6d592eaee987723e13c4d9be2f1d1433eda3e5b8d1d4479731698997bc3af11a
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