Instructions to use lethalantidote/phi-detector-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lethalantidote/phi-detector-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="lethalantidote/phi-detector-model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("lethalantidote/phi-detector-model") model = AutoModelForTokenClassification.from_pretrained("lethalantidote/phi-detector-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 452be4b2a6757e466cc7b32a009b287bc9f5e3be7558d8e2b607b82596faeb52
- Size of remote file:
- 436 MB
- SHA256:
- c8da8478c5d4ba0cdacd229827f96b0c8b34c54ba34a84d3c61ecb8b4f6d9294
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.