Instructions to use icpro/trained-model-classification-evaluation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use icpro/trained-model-classification-evaluation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="icpro/trained-model-classification-evaluation")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("icpro/trained-model-classification-evaluation") model = AutoModelForSequenceClassification.from_pretrained("icpro/trained-model-classification-evaluation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd0d370514e30d20e9a8ec7744195a399c5ae6518bc0f3bf4cd83da3f5801f39
- Size of remote file:
- 5.11 kB
- SHA256:
- 1ad47d0c5638d898b3cfab06f0ca33bb319addfae7f028a120bc771c06af6545
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