Instructions to use Etelis/TSE_XLNET_5E with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Etelis/TSE_XLNET_5E with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Etelis/TSE_XLNET_5E")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Etelis/TSE_XLNET_5E") model = AutoModelForSequenceClassification.from_pretrained("Etelis/TSE_XLNET_5E", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8a66dd179311151894af6a83a39d6e8e2b02f73b4245bd37c21386d7f1efde5e
- Size of remote file:
- 3.39 kB
- SHA256:
- 0bddd5b67cb14b42dec5e8ac601fda2df206222aba3774ce9d59a5bedd179b8f
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