Instructions to use ronka/postureDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ronka/postureDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ronka/postureDetection") 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("ronka/postureDetection") model = AutoModelForImageClassification.from_pretrained("ronka/postureDetection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download all_results.json from ronka/postureDetection: direct link, hf CLI and curl.
- Browser
- Download file 165 Bytes
-
https://huggingface.co/ronka/postureDetection/resolve/main/all_results.json
- Command line
-
hf download hf://ronka/postureDetection/all_results.json
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curl -L -o all_results.json https://huggingface.co/ronka/postureDetection/resolve/main/all_results.json
165 Bytes
| { | |
| "epoch": 4.0, | |
| "train_loss": 0.49794552226861316, | |
| "train_runtime": 44.8816, | |
| "train_samples_per_second": 3.298, | |
| "train_steps_per_second": 0.267 | |
| } |