Instructions to use Etelis/rtm_XLNET_5E with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Etelis/rtm_XLNET_5E with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Etelis/rtm_XLNET_5E")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Etelis/rtm_XLNET_5E") model = AutoModelForSequenceClassification.from_pretrained("Etelis/rtm_XLNET_5E", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fa39ca3424b91365a26b54ac21ad57de6fafbd935cc148bb1c38cfcd40a08e95
- Size of remote file:
- 3.38 kB
- SHA256:
- bf7e7bff61cf9d5de3ee49f3d5e3386d1c3ee6e1b06ac0c9d546598b126934ac
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