Instructions to use Aktsvigun/tmp_electra_large_aug_6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aktsvigun/tmp_electra_large_aug_6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Aktsvigun/tmp_electra_large_aug_6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Aktsvigun/tmp_electra_large_aug_6") model = AutoModelForSequenceClassification.from_pretrained("Aktsvigun/tmp_electra_large_aug_6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ba60fe6584a17b071d49dc5944a14bee3bd0b4fbe7c77bd159353bb9ae32504
- Size of remote file:
- 1.34 GB
- SHA256:
- 521fa93d5475903748ce14be45f55884c2d9f4493e14b0be1a32531018a60c82
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