Instructions to use Etelis/SST2_XLNET_5E with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Etelis/SST2_XLNET_5E with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Etelis/SST2_XLNET_5E")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Etelis/SST2_XLNET_5E") model = AutoModelForSequenceClassification.from_pretrained("Etelis/SST2_XLNET_5E", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d760d0f5ec027706eac70a0a0520b3e200f2d14e6a547a16063a37e1047ef18b
- Size of remote file:
- 469 MB
- SHA256:
- 55c7c7cfd06c6d5531b6fb50f543d10acdb9046e4c85240718b5dd60e13fdb12
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