Instructions to use google/tapas-base-masklm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-base-masklm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google/tapas-base-masklm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google/tapas-base-masklm") model = AutoModelForMaskedLM.from_pretrained("google/tapas-base-masklm") - Notebooks
- Google Colab
- Kaggle
TF model weights
Browse files- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:aaf790d71f1018ffcee3c44f16894d075a42cbb9697cdc193ed36f4b90c7808f
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size 543238192
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