Instructions to use boatp/intent_classify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use boatp/intent_classify with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="boatp/intent_classify")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("boatp/intent_classify") model = AutoModel.from_pretrained("boatp/intent_classify", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from boatp/intent_classify: direct link, hf CLI and curl.
- Browser
- Download file 17.6 MB
-
https://huggingface.co/boatp/intent_classify/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://boatp/intent_classify/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/boatp/intent_classify/resolve/main/pytorch_model.bin
17.6 MB
- Xet hash:
- e6237e430e56fea89af2ff047efe0ee7525cf1d9d366e0e0e80cf4e6b0a67e4f
- Size of remote file:
- 17.6 MB
- SHA256:
- 25f8712e1668edbadc38044b7a46caa2cde8b524d77a91ce9c217f6c6c6bb681
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