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:
- 330f47ddef67f422ee7fb127bf59b4d881ea8183c08905cf94089e88edbaa2cc
- Size of remote file:
- 3.38 kB
- SHA256:
- e17875f16162edc142f40fc0348854aa63934444e1aa55d1dfd529d9e0394041
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