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:
- 2bc0fbdb13ebf801c2566a0156026b6347d2af6e0fff020dee23eba77d3dfdce
- Size of remote file:
- 1.55 kB
- SHA256:
- 2301fccdc9e52fdcca132c2dd97de7c91e4cdb66e2e756c88d8744b7adabc784
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