Instructions to use eskayML/electra_interview_new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eskayML/electra_interview_new with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="eskayML/electra_interview_new")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("eskayML/electra_interview_new") model = AutoModelForSequenceClassification.from_pretrained("eskayML/electra_interview_new") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e3f317b40e282065728d31f1c6cad5556e2abf69f31a2d1d9513ebf05f0a13f
- Size of remote file:
- 5.3 kB
- SHA256:
- 16905a4f2f0464a8209f41eeb68c1d827eaebd9b151a36821496df2a75c6de56
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