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 pytorch_model.bin from brandaobrandisborges/layoutlm-synth2: direct link, hf CLI and curl.
- Browser
- Download file 451 MB
-
https://huggingface.co/brandaobrandisborges/layoutlm-synth2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://brandaobrandisborges/layoutlm-synth2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/brandaobrandisborges/layoutlm-synth2/resolve/main/pytorch_model.bin
451 MB
- Xet hash:
- 2b64ccff17fa6bb897572002420035b0b4b685c5a8cc4da81d068812f3c7f5c1
- Size of remote file:
- 451 MB
- SHA256:
- 83ad64cca04fadc0aeb94131a06677ad5f58fc1eff664a1a8dd6c6f090815695
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