Instructions to use csr2000/UCF_Crime with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use csr2000/UCF_Crime with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="csr2000/UCF_Crime") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("csr2000/UCF_Crime") model = AutoModelForImageClassification.from_pretrained("csr2000/UCF_Crime", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from csr2000/UCF_Crime: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/csr2000/UCF_Crime/resolve/main/training_args.bin
- Command line
-
hf download hf://csr2000/UCF_Crime/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/csr2000/UCF_Crime/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- dbf34a40b35b63a77752388070fe0cae99f841d647fe72e6ca72d477810df3a8
- Size of remote file:
- 3.31 kB
- SHA256:
- b13ea13db328c4d4cf4d52abcbbd75c345400590d75589e0600c7746b2517b35
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