Instructions to use Antdochi/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Antdochi/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Antdochi/results") 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("Antdochi/results") model = AutoModelForImageClassification.from_pretrained("Antdochi/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Antdochi/results: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/Antdochi/results/resolve/main/training_args.bin
- Command line
-
hf download hf://Antdochi/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Antdochi/results/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- c18596a8752bae2c92ade5583c5174a3355b23f441ed3baf3a3e89afc2aed9af
- Size of remote file:
- 4.09 kB
- SHA256:
- 31ff269fb58576101ccc5a11e24308830571eebb6ac739650ec0e1ea082a1978
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