Instructions to use brandaobrandisborges/layoutlm-synth3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brandaobrandisborges/layoutlm-synth3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="brandaobrandisborges/layoutlm-synth3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("brandaobrandisborges/layoutlm-synth3") model = AutoModelForTokenClassification.from_pretrained("brandaobrandisborges/layoutlm-synth3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from brandaobrandisborges/layoutlm-synth3: direct link, hf CLI and curl.
- Browser
- Download file 451 MB
-
https://huggingface.co/brandaobrandisborges/layoutlm-synth3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://brandaobrandisborges/layoutlm-synth3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/brandaobrandisborges/layoutlm-synth3/resolve/main/pytorch_model.bin
451 MB
- Xet hash:
- 471bac2df10eb7ee30e83bf7444d6b65fcdca4b2469255d572c53f5e85d20b7c
- Size of remote file:
- 451 MB
- SHA256:
- 0420a97687ea79e83c93f53af9b855aa7fa0dc421358e9b8637bf72eccf62039
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