Instructions to use tradero/distilbert-user-intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tradero/distilbert-user-intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tradero/distilbert-user-intent")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tradero/distilbert-user-intent") model = AutoModelForSequenceClassification.from_pretrained("tradero/distilbert-user-intent") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c04b759903b2dd784bdcca3542cde779c8b4a1c90d5fb257e9aedee123ab8858
- Size of remote file:
- 557 MB
- SHA256:
- 85e09010310e6cd5724034100554c74af99708c6daff931e0364ced62bc74451
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