Instructions to use agent593/content with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agent593/content with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="agent593/content") 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("agent593/content") model = AutoModelForImageClassification.from_pretrained("agent593/content", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from agent593/content: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/agent593/content/resolve/main/training_args.bin
- Command line
-
hf download hf://agent593/content/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/agent593/content/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 72ed2b2578d33cbd131b7398a96b0cf8ced79ad3336a84af4a0fc39fe6e537f1
- Size of remote file:
- 5.05 kB
- SHA256:
- 4047f8a6216bb0d2a3319c4fc5ee26be2d7b7c30cfd9c960caf559a764141bf1
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