Instructions to use AbstractQbit/electra_large_imdb_htsplice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AbstractQbit/electra_large_imdb_htsplice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AbstractQbit/electra_large_imdb_htsplice")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AbstractQbit/electra_large_imdb_htsplice") model = AutoModelForSequenceClassification.from_pretrained("AbstractQbit/electra_large_imdb_htsplice", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93ad8a6fa4dc4860f816e99811fde3c5984ccb3f08fed2773ba4cd0c10e3a584
- Size of remote file:
- 2.68 GB
- SHA256:
- 585dfd8f3e2227c2e8d4f41107da6b7e73b07aeef18cb8dd1d39405923fb86b6
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