Instructions to use mlovelli/intent_classifier_bert_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlovelli/intent_classifier_bert_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mlovelli/intent_classifier_bert_base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mlovelli/intent_classifier_bert_base") model = AutoModelForSequenceClassification.from_pretrained("mlovelli/intent_classifier_bert_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 12bd94d53d5c58d913ffa4abac6eb77718a7df7efa228c831d08c8cf2c4bcdff
- Size of remote file:
- 433 MB
- SHA256:
- 40759c251404ff6c1eaab25d4cdbda900a25d378d4c9a67433fd6e1500569999
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