Instructions to use romin23/lilt-form-read with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use romin23/lilt-form-read with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="romin23/lilt-form-read")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("romin23/lilt-form-read") model = AutoModelForTokenClassification.from_pretrained("romin23/lilt-form-read", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1100b7831fc296ce1ce2a7900d6b0381da1991a6498d0e8d3f2ef327e10e30e9
- Size of remote file:
- 521 MB
- SHA256:
- 869b2d6233f37f30ad5f767df40121a650dce5c029bed3c053a82b723facec74
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