Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use Ahmed235/roberta-base-topic_classification_simple2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ahmed235/roberta-base-topic_classification_simple2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ahmed235/roberta-base-topic_classification_simple2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ahmed235/roberta-base-topic_classification_simple2") model = AutoModelForSequenceClassification.from_pretrained("Ahmed235/roberta-base-topic_classification_simple2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2407745b922c8c3e925ec57a4d68ca0b1d28fac279e9b57bcda8ea63b95da027
- Size of remote file:
- 4.79 kB
- SHA256:
- 5551030a00a0aee28032d4365a44b2617de6fa5fb681a5f73269a2dbb08bb864
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