Instructions to use MariaK/my-lilt-en-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MariaK/my-lilt-en-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="MariaK/my-lilt-en-funsd")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("MariaK/my-lilt-en-funsd") model = AutoModelForTokenClassification.from_pretrained("MariaK/my-lilt-en-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MariaK/my-lilt-en-funsd: direct link, hf CLI and curl.
- Browser
- Download file 521 MB
-
https://huggingface.co/MariaK/my-lilt-en-funsd/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MariaK/my-lilt-en-funsd/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MariaK/my-lilt-en-funsd/resolve/main/pytorch_model.bin
521 MB
- Xet hash:
- 6cf53154f6df5323aa7109665087faa8afcb99c3d9c5c8cdcceae24beed78607
- Size of remote file:
- 521 MB
- SHA256:
- 850f630f21533d1729241ab825a7119ec695e7e4ba575482440d3c7884243eb6
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