Instructions to use LinusReply/lilt-en-funsd-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LinusReply/lilt-en-funsd-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="LinusReply/lilt-en-funsd-2")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("LinusReply/lilt-en-funsd-2") model = AutoModelForTokenClassification.from_pretrained("LinusReply/lilt-en-funsd-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 149122248a21092a13187c3b31e0fd866a877603a9940d92ef0f1567999eed03
- Size of remote file:
- 521 MB
- SHA256:
- 9382cd3273e3f6397eebcc99914a4d9dad3ebb9e590de8521a7e0f838ab92607
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