Instructions to use dbmdz/bert-base-historic-multilingual-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dbmdz/bert-base-historic-multilingual-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="dbmdz/bert-base-historic-multilingual-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("dbmdz/bert-base-historic-multilingual-cased") model = AutoModelForMaskedLM.from_pretrained("dbmdz/bert-base-historic-multilingual-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
readme: mention smaller models
Browse files
README.md
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| Finnish | [Europeana](http://www.europeana-newspapers.eu/) | 1.2GB
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| Swedish | [Europeana](http://www.europeana-newspapers.eu/) | 1.1GB
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## Models
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| Model identifier
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| `dbmdz/bert-
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| `dbmdz/bert-
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| `dbmdz/bert-
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| `dbmdz/bert-
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# Corpora Stats
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| Finnish | [Europeana](http://www.europeana-newspapers.eu/) | 1.2GB
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| Swedish | [Europeana](http://www.europeana-newspapers.eu/) | 1.1GB
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## Smaller Models
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We have also released smaller models for the multilingual model:
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| Model identifier | Model Hub link
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| `dbmdz/bert-tiny-historic-multilingual-cased` | [here](https://huggingface.co/dbmdz/bert-tiny-historic-multilingual-cased)
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| `dbmdz/bert-mini-historic-multilingual-cased` | [here](https://huggingface.co/dbmdz/bert-mini-historic-multilingual-cased)
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| `dbmdz/bert-small-historic-multilingual-cased` | [here](https://huggingface.co/dbmdz/bert-small-historic-multilingual-cased)
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| `dbmdz/bert-medium-historic-multilingual-cased` | [here](https://huggingface.co/dbmdz/bert-base-historic-multilingual-cased)
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# Corpora Stats
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