Instructions to use brandaobrandisborges/layoutlm-synthchecking with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brandaobrandisborges/layoutlm-synthchecking with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="brandaobrandisborges/layoutlm-synthchecking")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("brandaobrandisborges/layoutlm-synthchecking") model = AutoModelForTokenClassification.from_pretrained("brandaobrandisborges/layoutlm-synthchecking", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from brandaobrandisborges/layoutlm-synthchecking: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/brandaobrandisborges/layoutlm-synthchecking/resolve/main/training_args.bin
- Command line
-
hf download hf://brandaobrandisborges/layoutlm-synthchecking/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/brandaobrandisborges/layoutlm-synthchecking/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- 4251d59f3dd61b863af7fad79a79dac501d16cd7c5ba2536c4ebe62f4f71dd3c
- Size of remote file:
- 3.58 kB
- SHA256:
- 0e9736fd9fe5af28eedb33462d7cadbb12e279de257edd78014e053d4c7ed88e
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