Instructions to use mlovelli/intent_classifier_deberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlovelli/intent_classifier_deberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mlovelli/intent_classifier_deberta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mlovelli/intent_classifier_deberta") model = AutoModelForSequenceClassification.from_pretrained("mlovelli/intent_classifier_deberta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff3e6244dcb1ad30e14acaf614c1f8e9592d24f53fc42abe4c8d75951c935dea
- Size of remote file:
- 738 MB
- SHA256:
- 795f3f84ad13c1a9f9dbc86cd68599d2d82d65358de4472242ed8275daa2c8f3
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