Instructions to use Aktsvigun/roberta_large_cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aktsvigun/roberta_large_cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Aktsvigun/roberta_large_cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Aktsvigun/roberta_large_cola") model = AutoModelForSequenceClassification.from_pretrained("Aktsvigun/roberta_large_cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29c45826dd528c22982ed7353d07918d46d0b160db6619ec94e680036773c056
- Size of remote file:
- 1.42 GB
- SHA256:
- 101d283a4d5f0e846394648fd55b243a834a304a79240f45c7b5a30fc6d5d6dc
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