Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Ahmed235/roberta-base-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ahmed235/roberta-base-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ahmed235/roberta-base-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ahmed235/roberta-base-classification") model = AutoModelForSequenceClassification.from_pretrained("Ahmed235/roberta-base-classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13e859ccbfaf32a492bb05e0c45a9c6fd8146883ae923bb92380c9af888520c3
- Size of remote file:
- 4.73 kB
- SHA256:
- f8ca90080eff099063a9e4f64bd568b92ab4f3592bae85a2cb0dd40ff4f93199
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