Text Classification
Transformers
Safetensors
English
phi3
safety
moderation
hazard-classification
custom_code
Instructions to use RavindraSingh22/phi-hazard-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RavindraSingh22/phi-hazard-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RavindraSingh22/phi-hazard-classifier", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("RavindraSingh22/phi-hazard-classifier", trust_remote_code=True) model = AutoModelForSequenceClassification.from_pretrained("RavindraSingh22/phi-hazard-classifier", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51e6bfa739adbf032401a112a18009da5b2b29c0fa3992001c711d19474684d6
- Size of remote file:
- 15.5 MB
- SHA256:
- d89e3c30dcce2f758d2dc54b80ce04731d9356eedf552bfe87eba5bf6d308c14
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.