Instructions to use mlovelli/intent_classifier_bert_base_less_eval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mlovelli/intent_classifier_bert_base_less_eval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mlovelli/intent_classifier_bert_base_less_eval")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mlovelli/intent_classifier_bert_base_less_eval") model = AutoModelForSequenceClassification.from_pretrained("mlovelli/intent_classifier_bert_base_less_eval", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c848656fdc35b7920ca42c259b3139a7f22e9e656d839e986f46c07a21098c3a
- Size of remote file:
- 433 MB
- SHA256:
- ee8da89bee21542e710d5d7005fecd439219caa9e08ec47c419d97382baa2297
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