Instructions to use mrfriedpotato/effect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrfriedpotato/effect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrfriedpotato/effect")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrfriedpotato/effect") model = AutoModelForSequenceClassification.from_pretrained("mrfriedpotato/effect") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf009c50027d80321132a392ecebdbb32b200345fcd808a7f08b76f06464c924
- Size of remote file:
- 438 MB
- SHA256:
- cce94ac06983d4119316aae6439f999810bf8390512c1d37be873991f7cdf078
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