Instructions to use brandaobrandisborges/layoutlm-synth2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brandaobrandisborges/layoutlm-synth2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="brandaobrandisborges/layoutlm-synth2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("brandaobrandisborges/layoutlm-synth2") model = AutoModelForTokenClassification.from_pretrained("brandaobrandisborges/layoutlm-synth2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from brandaobrandisborges/layoutlm-synth2: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/brandaobrandisborges/layoutlm-synth2/resolve/main/training_args.bin
- Command line
-
hf download hf://brandaobrandisborges/layoutlm-synth2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/brandaobrandisborges/layoutlm-synth2/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- 923fe33a5aeb20c36cccc6e8bb552a292dc878fbf54de294b7fa3dbb31723e94
- Size of remote file:
- 3.58 kB
- SHA256:
- 69a80397d2eaf6bedbb394aab25f13cef635e5e64878e7dde72979aad7ae2036
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