Instructions to use itzfiza2026/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use itzfiza2026/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="itzfiza2026/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("itzfiza2026/results") model = AutoModelForSequenceClassification.from_pretrained("itzfiza2026/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a06ae7c0bc5ae74c7932aa59b78f3122461cf9a803bc66f5d17db8467b846d0
- Size of remote file:
- 5.65 kB
- SHA256:
- 42dc68c8bc840ad6fa484b2a8c1964e851cb41000d5d0d27c0ee28464aeeaeb9
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