Instructions to use ModelTC/roberta-base-qqp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/roberta-base-qqp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/roberta-base-qqp")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/roberta-base-qqp") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/roberta-base-qqp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 612aa681c65b782a0548f7591b902ac1864155082aa1397a1f1142a8f5ba68ca
- Size of remote file:
- 3.06 kB
- SHA256:
- 623a732a7df841aca79acda727b6d6729b0dd201503704284ddd2afe22e51a0c
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