Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use Umesh/police-lethal-force-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Umesh/police-lethal-force-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Umesh/police-lethal-force-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Umesh/police-lethal-force-classifier") model = AutoModelForSequenceClassification.from_pretrained("Umesh/police-lethal-force-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Umesh/police-lethal-force-classifier: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Umesh/police-lethal-force-classifier/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Umesh/police-lethal-force-classifier@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Umesh/police-lethal-force-classifier/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- 98cafa81a576179035c59560d350205f2debedf221a1932e33b3fce7e8508e9e
- Size of remote file:
- 438 MB
- SHA256:
- 6c928df77da7ed378a9c86e689f9747256932b433d3da12be7df74a618a53e40
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