Instructions to use Porameht/bert-base-multilingual-cased-intent-booking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Porameht/bert-base-multilingual-cased-intent-booking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Porameht/bert-base-multilingual-cased-intent-booking")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Porameht/bert-base-multilingual-cased-intent-booking") model = AutoModelForSequenceClassification.from_pretrained("Porameht/bert-base-multilingual-cased-intent-booking") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 433fb2e669aae37ac674522e9858632b53c5250e5bf06c6c2d151e74afe8ab21
- Size of remote file:
- 5.24 kB
- SHA256:
- 1c3a5fa3c4a91f923c1057b39548fe59c4aa11af52a525fd4148e95b6be234a5
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