Instructions to use gianma/classifierDomAugmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gianma/classifierDomAugmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gianma/classifierDomAugmented")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("gianma/classifierDomAugmented") model = AutoModelForSequenceClassification.from_pretrained("gianma/classifierDomAugmented") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71f80fbb54118a1d5eed8d2485a7b38c144810a6c3b0329c1e405bb1f850b140
- Size of remote file:
- 443 MB
- SHA256:
- c7be1139e2a069364f20886f8a916f77bae496d055684b1101e73ae757295c59
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