Instructions to use EmnaBou/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EmnaBou/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="EmnaBou/results")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("EmnaBou/results") model = AutoModelForTokenClassification.from_pretrained("EmnaBou/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30d5635c1650f46c609767bc3e021bc50ba3f9c07c5049cc5638e86805c587b0
- Size of remote file:
- 441 MB
- SHA256:
- a456dd6101a71bda149f68d5781cfb4cebe97d3c2b8c2577bf561bc9c15fda1b
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