Instructions to use Etelis/TUF_XLNET_5E with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Etelis/TUF_XLNET_5E with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Etelis/TUF_XLNET_5E")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Etelis/TUF_XLNET_5E") model = AutoModelForSequenceClassification.from_pretrained("Etelis/TUF_XLNET_5E", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Etelis/TUF_XLNET_5E: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/Etelis/TUF_XLNET_5E/resolve/main/training_args.bin
- Command line
-
hf download hf://Etelis/TUF_XLNET_5E/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Etelis/TUF_XLNET_5E/resolve/main/training_args.bin
3.39 kB
- Xet hash:
- f3ee434439b3fe24fb766479936e155d6cdcd0f786374ad47ab5167c38faba72
- Size of remote file:
- 3.39 kB
- SHA256:
- 2d3fde3b5dc6946811e9792f7885e06f32e484b50228698f511c75f69a2a98f7
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