Instructions to use Etelis/CR_XLNET_5E with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Etelis/CR_XLNET_5E with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Etelis/CR_XLNET_5E")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Etelis/CR_XLNET_5E") model = AutoModelForSequenceClassification.from_pretrained("Etelis/CR_XLNET_5E", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Etelis/CR_XLNET_5E: direct link, hf CLI and curl.
- Browser
- Download file 3.39 kB
-
https://huggingface.co/Etelis/CR_XLNET_5E/resolve/main/training_args.bin
- Command line
-
hf download hf://Etelis/CR_XLNET_5E/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Etelis/CR_XLNET_5E/resolve/main/training_args.bin
3.39 kB
- Xet hash:
- 2019f874e7fa81a785e20c8d35030061130bc6d79292a648d38c4dba8e8fcc45
- Size of remote file:
- 3.39 kB
- SHA256:
- f1b5dec72073ad247a756e34860a10e89faba2a2fdb60131cb940199136d522a
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