Instructions to use idirectships/abacus-cheat-tell-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use idirectships/abacus-cheat-tell-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="idirectships/abacus-cheat-tell-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("idirectships/abacus-cheat-tell-v1") model = AutoModelForSequenceClassification.from_pretrained("idirectships/abacus-cheat-tell-v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d932cbc2ae97e0ec3d7ecc037c5513c36e086b752f894b6c7f808addc0090b12
- Size of remote file:
- 598 MB
- SHA256:
- c7bfe35b10f70bd2b423845bf48fb3f42bdbd83bdf82b30d4162012e6aecfb3d
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