Instructions to use Shruthikaa/FNet_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shruthikaa/FNet_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Shruthikaa/FNet_Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Shruthikaa/FNet_Classification") model = AutoModelForSequenceClassification.from_pretrained("Shruthikaa/FNet_Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e1430f87b91b45da07c3fe9ab6c7e8add121c260871a031d58e380baab4e7b7
- Size of remote file:
- 4.54 kB
- SHA256:
- c4b3c3289a93e95db4784e40af7830dd76b067d50d6ec848c2667888e4bb65df
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