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:
- f1ea5e51234001b1f87135c376d3e20969afdd40ff6bdf31f8d46855f8ef6c8b
- Size of remote file:
- 997 MB
- SHA256:
- ed8dd2655c8a3227c36f2923c26e803748cf4f8ce86e33ff2419fb6a235f566f
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