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:
- 6d83e4beb4298ba19df774b3e1e78490d45dd7577c3491688a51571858da0481
- Size of remote file:
- 54.2 MB
- SHA256:
- 3894cfe4f3735a911a25d70b1c53da6bae76d75cbf5fd9839564037f9b0f8b89
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