Instructions to use JeswinMS4/bert-base-intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeswinMS4/bert-base-intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeswinMS4/bert-base-intent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeswinMS4/bert-base-intent") model = AutoModelForSequenceClassification.from_pretrained("JeswinMS4/bert-base-intent") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 613b67b2dc573b586d2e1f1b897d3509efbeacf59f03e9b00d1912ad0f553b2c
- Size of remote file:
- 438 MB
- SHA256:
- 8be1d35ce45556374c01dca8911a3e929586744077c7485865665abad9272c6e
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