Instructions to use eyaHarbaoui/markuplmForNER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eyaHarbaoui/markuplmForNER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="eyaHarbaoui/markuplmForNER")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("eyaHarbaoui/markuplmForNER") model = AutoModelForTokenClassification.from_pretrained("eyaHarbaoui/markuplmForNER") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a54873d8d2fad7eaa621b9bb5d3924527630cc1d02468f9309caf43d6f350d46
- Size of remote file:
- 539 MB
- SHA256:
- b706d05e5c7eba474e3917a08eab7ec0b1487f1751ff65b20c1eadb9798b569d
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