Translation
Transformers
Safetensors
Czech
German
mt5
text2text-generation
code
wikidata
biography
semantic_annotation
entity_linking
Instructions to use daelba/biography2wikidata with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use daelba/biography2wikidata with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="daelba/biography2wikidata")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("daelba/biography2wikidata") model = AutoModelForSeq2SeqLM.from_pretrained("daelba/biography2wikidata", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Verified signatureA model for annotating entries in biographical dictionaries using Wikidata entities. Based on <a href="https://huggingface.co/google/mt5-small">Google's mT5</a>. Example input text: <code>Anschiringer, Anton, Publizist, * 1812 Wien, † 17. 12. 1873 Reichenberg (Liberec). Erzieher im Hause des Großindustriellen...</code> Example output text: <code>{{WD|label|Anschiringer, Anton}}, {{WD|P106|Q6051619|Publizist}}, * {{WD|P569|1812}} {{WD|P19|Q1741|Wien}}, † {{WD|P570|1873-12-17|17. 12. 1873}} {{WD|P20|Q2978|Richenberg (Liberec)}}. Erzieher im Hause des Großindustriellen...</code>1c2f1a0 -
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