Instructions to use brandaobrandisborges/layoutlm-synth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brandaobrandisborges/layoutlm-synth with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="brandaobrandisborges/layoutlm-synth")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("brandaobrandisborges/layoutlm-synth") model = AutoModelForTokenClassification.from_pretrained("brandaobrandisborges/layoutlm-synth", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from brandaobrandisborges/layoutlm-synth: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/brandaobrandisborges/layoutlm-synth/resolve/main/training_args.bin
- Command line
-
hf download hf://brandaobrandisborges/layoutlm-synth/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/brandaobrandisborges/layoutlm-synth/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- 103203e2a5c835c843af94dfd661ef2a1a78c7c8e6191d65541521468fe3bf8c
- Size of remote file:
- 3.58 kB
- SHA256:
- f1ebec62277c945a33d283dfac961c93169798237d04e5322b46c94396338e2f
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