Instructions to use Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice") model = AutoModelForTokenClassification.from_pretrained("Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice: direct link, hf CLI and curl.
- Browser
- Download file 3.25 kB
-
https://huggingface.co/Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice/resolve/main/training_args.bin
- Command line
-
hf download hf://Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ammar-alhaj-ali/LayoutLMv3-Fine-Tuning-Invoice/resolve/main/training_args.bin
3.25 kB
- Xet hash:
- 93607073f4dfd81334a61022284369956365130c170a25b57baff42f24c52d23
- Size of remote file:
- 3.25 kB
- SHA256:
- 728a96c34b9e0252a7d161e1af57942ae1f0ec4872e2e5f724504b188ee5aeb9
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