Instructions to use aw2323/multi_intents_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aw2323/multi_intents_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aw2323/multi_intents_classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aw2323/multi_intents_classification") model = AutoModelForSequenceClassification.from_pretrained("aw2323/multi_intents_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fca3180db715a77f41adc1f9a31af15ad8871b02cfe3cc77361b8802fd0a23ce
- Size of remote file:
- 17.1 MB
- SHA256:
- 1ae4ad906c12d1a30042e08b31100566bcbff476dbe7eef915dbf3575acd437c
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