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:
- 5d9f894f3693bdcedb3478371cdace519cc457fd6f250a4db6c7206cc13e96b9
- Size of remote file:
- 3.71 kB
- SHA256:
- f786e36e587f57aa16e36e866bdbaa5961b59563fddb5e05c500499e1282f912
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