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:
- 184fa2300610f1ed519c2607b46b03e617c6abadb134623babcd8b621f2a9730
- Size of remote file:
- 623 Bytes
- SHA256:
- 80e512717c051bd5ada11c1d32a5e524e6add99637caa37481aa1461115864b4
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