Instructions to use Aktsvigun/roberta_cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aktsvigun/roberta_cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Aktsvigun/roberta_cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Aktsvigun/roberta_cola") model = AutoModelForSequenceClassification.from_pretrained("Aktsvigun/roberta_cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 186c17230fe3058f9d812a641f2bbd690b7af4badd00dd3f555e75a9a4a5c6d6
- Size of remote file:
- 1.74 GB
- SHA256:
- 512e4fa21d7145b9019f379dc1c01323a18b9d027774a4c5c829e02cb346dcd1
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