Instructions to use Resi/layoutlmv3-multilabel-v2-colab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Resi/layoutlmv3-multilabel-v2-colab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Resi/layoutlmv3-multilabel-v2-colab")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("Resi/layoutlmv3-multilabel-v2-colab") model = AutoModelForTokenClassification.from_pretrained("Resi/layoutlmv3-multilabel-v2-colab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Resi/layoutlmv3-multilabel-v2-colab: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/Resi/layoutlmv3-multilabel-v2-colab/resolve/main/tokenizer.json
- Command line
-
hf download hf://Resi/layoutlmv3-multilabel-v2-colab/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Resi/layoutlmv3-multilabel-v2-colab/resolve/main/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.