Instructions to use gary2002/output_dir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gary2002/output_dir with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gary2002/output_dir") 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("gary2002/output_dir") model = AutoModelForImageClassification.from_pretrained("gary2002/output_dir", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download train_results.json from gary2002/output_dir: direct link, hf CLI and curl.
- Browser
- Download file 208 Bytes
-
https://huggingface.co/gary2002/output_dir/resolve/main/train_results.json
- Command line
-
hf download hf://gary2002/output_dir/train_results.json
-
curl -L -o train_results.json https://huggingface.co/gary2002/output_dir/resolve/main/train_results.json
208 Bytes
| { | |
| "epoch": 3.0, | |
| "total_flos": 1.6948561394167603e+17, | |
| "train_loss": 0.7343477571391623, | |
| "train_runtime": 162.6903, | |
| "train_samples_per_second": 13.443, | |
| "train_steps_per_second": 1.346 | |
| } |