Instructions to use Livingwithmachines/bert_1890_1900 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Livingwithmachines/bert_1890_1900 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Livingwithmachines/bert_1890_1900")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Livingwithmachines/bert_1890_1900") model = AutoModelForMaskedLM.from_pretrained("Livingwithmachines/bert_1890_1900", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8064dc4eabd5d03b28f5955276ef0a7aac23d44fc06539f14acc6543d6defac5
- Size of remote file:
- 440 MB
- SHA256:
- 03261e061d718fe3db7382e61cdfb37d47ef33b45f84c2bae08c8a62648f64c9
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