Instructions to use Crayo1902/XLNET with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Crayo1902/XLNET with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Crayo1902/XLNET")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Crayo1902/XLNET") model = AutoModelForSequenceClassification.from_pretrained("Crayo1902/XLNET", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39281a5e08389db48ff6a725fead9aa4bd4b94667b6fcd438d4bbfa28b3676b5
- Size of remote file:
- 469 MB
- SHA256:
- 9ac88389e7bf53124f2cfc18f48970fb70f32a3308857357078713814e32b32b
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