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:
- 995ac78979d2a2e38abff4dfdf456c845e0865760b5c9eb5b9297dcc60b8a05a
- Size of remote file:
- 3.96 kB
- SHA256:
- 84af778c4560991036c32af37c88513179c520a841ede123e96058af94373cb2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.