Instructions to use rcds/MiniLM-swiss_citation_extraction-de-fr-it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rcds/MiniLM-swiss_citation_extraction-de-fr-it with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="rcds/MiniLM-swiss_citation_extraction-de-fr-it")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("rcds/MiniLM-swiss_citation_extraction-de-fr-it") model = AutoModelForTokenClassification.from_pretrained("rcds/MiniLM-swiss_citation_extraction-de-fr-it", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64d478513310dbc363d6c187f3d13282d61f5b8482ea52d388be0645f2edc27c
- Size of remote file:
- 960 MB
- SHA256:
- 98d732e378ec11d5346171b8e9b1d5e9e266b77ec17192d7e366ad128f1f71a6
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