Instructions to use K1Alex/losdtos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use K1Alex/losdtos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="K1Alex/losdtos") 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("K1Alex/losdtos") model = AutoModelForImageClassification.from_pretrained("K1Alex/losdtos", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from K1Alex/losdtos: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/K1Alex/losdtos/resolve/main/training_args.bin
- Command line
-
hf download hf://K1Alex/losdtos/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/K1Alex/losdtos/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 0eea14fd387927b9012b57aec43690b9ea686af72f40eff1dbebf63d7e5dd213
- Size of remote file:
- 5.18 kB
- SHA256:
- 54e4246f6accee9a1a92b38aee8531c5da4119a74cfeb6959082eaeb43a5b4d2
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