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 training_args.bin from Umesh/police-lethal-force-classifier: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/Umesh/police-lethal-force-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://Umesh/police-lethal-force-classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Umesh/police-lethal-force-classifier/resolve/main/training_args.bin
3.52 kB
- Xet hash:
- 3861d3c1223846ee122a233408864ce92a0ff3d9a2c0b1a8760840b2046f0fe4
- Size of remote file:
- 3.52 kB
- SHA256:
- de437b4effff2fca17ddac72aeb8af069ceb389c9571d2c00d5525a6411413a9
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