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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tradero/distilbert-user-intent") model = AutoModelForSequenceClassification.from_pretrained("tradero/distilbert-user-intent", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tradero/distilbert-user-intent: direct link, hf CLI and curl.
- Browser
- Download file 557 MB
-
https://huggingface.co/tradero/distilbert-user-intent/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tradero/distilbert-user-intent/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tradero/distilbert-user-intent/resolve/main/pytorch_model.bin
557 MB
- Xet hash:
- c04b759903b2dd784bdcca3542cde779c8b4a1c90d5fb257e9aedee123ab8858
- Size of remote file:
- 557 MB
- SHA256:
- 85e09010310e6cd5724034100554c74af99708c6daff931e0364ced62bc74451
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