Instructions to use anileo1/phi4-mini-classifier-lora-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anileo1/phi4-mini-classifier-lora-v1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("anileo1/phi4-mini-classifier-lora-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from anileo1/phi4-mini-classifier-lora-v1: direct link, hf CLI and curl.
- Browser
- Download file 15.5 MB
-
https://huggingface.co/anileo1/phi4-mini-classifier-lora-v1/resolve/main/tokenizer.json
- Command line
-
hf download hf://anileo1/phi4-mini-classifier-lora-v1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/anileo1/phi4-mini-classifier-lora-v1/resolve/main/tokenizer.json
15.5 MB
- Xet hash:
- 0e0643acc564bb0bb41e1fc82b35b0bd1824a89e58d3969295aa23a3d1d373d5
- Size of remote file:
- 15.5 MB
- SHA256:
- 382cc235b56c725945e149cc25f191da667c836655efd0857b004320e90e91ea
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.