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:
- 0b89f383b8c5d9d2e38585d615cc71c9243f71347cd7e2523af0f7988491328f
- Size of remote file:
- 234 MB
- SHA256:
- 4fb8c2f3783bbb46fda017839c53b91da2470cddf11a8aca72ed424f3c8ff23d
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