Instructions to use mathieu1256/layoutlmv3-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mathieu1256/layoutlmv3-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="mathieu1256/layoutlmv3-test")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("mathieu1256/layoutlmv3-test") model = AutoModelForTokenClassification.from_pretrained("mathieu1256/layoutlmv3-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download train_results.json from mathieu1256/layoutlmv3-test: direct link, hf CLI and curl.
- Browser
- Download file 191 Bytes
-
https://huggingface.co/mathieu1256/layoutlmv3-test/resolve/main/train_results.json
- Command line
-
hf download hf://mathieu1256/layoutlmv3-test/train_results.json
-
curl -L -o train_results.json https://huggingface.co/mathieu1256/layoutlmv3-test/resolve/main/train_results.json
191 Bytes
| { | |
| "epoch": 0.0, | |
| "train_loss": 1.4569509029388428, | |
| "train_runtime": 29.2044, | |
| "train_samples": 8600, | |
| "train_samples_per_second": 0.274, | |
| "train_steps_per_second": 0.034 | |
| } |