Instructions to use SaiPavanKumarMeruga/roberta-base-lora-sarcasm-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SaiPavanKumarMeruga/roberta-base-lora-sarcasm-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SaiPavanKumarMeruga/roberta-base-lora-sarcasm-classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SaiPavanKumarMeruga/roberta-base-lora-sarcasm-classification") model = AutoModelForSequenceClassification.from_pretrained("SaiPavanKumarMeruga/roberta-base-lora-sarcasm-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 666e4e9d9f9a636fc4e7fe83741015094e9318573990f9ff8f6162d1b0b1cba6
- Size of remote file:
- 501 MB
- SHA256:
- 30b3b022603ae1e6818aa256dc60a7ba0cad0c03d10191fa0e3a1d6e2c55091c
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