Instructions to use ffgcc/condenser-bert-large-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ffgcc/condenser-bert-large-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ffgcc/condenser-bert-large-uncased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ffgcc/condenser-bert-large-uncased") model = AutoModelForMaskedLM.from_pretrained("ffgcc/condenser-bert-large-uncased") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 143251e7f6643893e868408f7182110ecad915ebeb9727c2ae3e99ba51ee50d6
- Size of remote file:
- 2.1 kB
- SHA256:
- 24bea9cf3699fb2c604b7ccd7ab5e75b924064eed084c50ed5609946abd63d9b
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