Instructions to use philschmid/lilt-en-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/lilt-en-funsd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="philschmid/lilt-en-funsd")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("philschmid/lilt-en-funsd") model = AutoModelForTokenClassification.from_pretrained("philschmid/lilt-en-funsd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1572e575f3ea52db61062809a06de8176020acfba113b0b8d174ae239d199a70
- Size of remote file:
- 521 MB
- SHA256:
- 4828206bf3def0bc143a6a03220e6104ebd0389f016efcc4b2b44ed1e1dc5fa0
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