Instructions to use cngchis/phi4-mini-intent with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cngchis/phi4-mini-intent with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cngchis/phi4-mini-intent")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("cngchis/phi4-mini-intent") model = AutoModelForCausalLM.from_pretrained("cngchis/phi4-mini-intent") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d564788a000062b1fd87b62dd85256d6055f152744f97629ad9711fdbe7df16
- Size of remote file:
- 15.5 MB
- SHA256:
- 37b10016a39382ff2d24acc20a291ed83243a26c4549ab01f6240e72c6291d56
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.