Instructions to use adity12345/roberta-classifier_batch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adity12345/roberta-classifier_batch32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="adity12345/roberta-classifier_batch32")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("adity12345/roberta-classifier_batch32") model = AutoModelForSequenceClassification.from_pretrained("adity12345/roberta-classifier_batch32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- febc7c1d1b2a039f547ef73a31dbf45146df3e619da08fe51b3cbe2d656dee67
- Size of remote file:
- 1.62 GB
- SHA256:
- ed6cea0e7d9edf110e29d7503c3f3e94a1012a1218dff75a61c252a1577e9cae
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