Instructions to use plexatic/ultrawhack-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use plexatic/ultrawhack-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="plexatic/ultrawhack-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("plexatic/ultrawhack-model") model = AutoModelForSequenceClassification.from_pretrained("plexatic/ultrawhack-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 18be65c7d2501d2b36834e1ecd87776afcd3f3856e0279380b83b748af0a6f0b
- Size of remote file:
- 2.24 GB
- SHA256:
- 9f7252032a8e646e06981833dae87fd089e0952e30e3c9e9a3f0bc3a6b0e4c99
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