Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Ahmed235/roberta-base-topic_classification_simple with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ahmed235/roberta-base-topic_classification_simple with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ahmed235/roberta-base-topic_classification_simple")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ahmed235/roberta-base-topic_classification_simple") model = AutoModelForSequenceClassification.from_pretrained("Ahmed235/roberta-base-topic_classification_simple") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 103b58d70631365256e8ad82378861c6704ec7696f5f57b62d0067eef54bc046
- Size of remote file:
- 4.79 kB
- SHA256:
- b8bdaff900886f4cbd7f05f842969c341e5a11061c14b776261c97444318c869
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