Instructions to use google/tapas-medium-masklm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-medium-masklm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google/tapas-medium-masklm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google/tapas-medium-masklm") model = AutoModelForMaskedLM.from_pretrained("google/tapas-medium-masklm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a43de8b51556e373c538444e488818fe4257dee3e25b18e56eaa6d5196e8a6e9
- Size of remote file:
- 168 MB
- SHA256:
- a48f88c89885945ec1e0906fbe84d4d1f9470ce321bb4a9385df3e89edea27bf
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