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:
- 059e3afa68711a470bea345da251b090775b3ad789a842487f74d625481276d3
- Size of remote file:
- 3.39 kB
- SHA256:
- b508bae15b8f2727fa23d64816b829ba8a544280ce2469dcfbc5395073d3ae1d
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