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 pytorch_model.bin from Antdochi/results: direct link, hf CLI and curl.
- Browser
- Download file 171 MB
-
https://huggingface.co/Antdochi/results/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Antdochi/results/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Antdochi/results/resolve/main/pytorch_model.bin
171 MB
- Xet hash:
- 1855133a3838c20b402ea326496cbb96426c2e88de3aebbbcde25c693f0832ef
- Size of remote file:
- 171 MB
- SHA256:
- 69cf7faa862dabe8978fd88463ec113d839d50211b3a857d13546b506d40f62c
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