Instructions to use google/tapas-tiny-masklm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/tapas-tiny-masklm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google/tapas-tiny-masklm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google/tapas-tiny-masklm") model = AutoModelForMaskedLM.from_pretrained("google/tapas-tiny-masklm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e7b54b1d4708d9498e7432a116e429bc44cdeff307f77314cbd8d69747ddbc83
- Size of remote file:
- 18.2 MB
- SHA256:
- 92204a96c0bdff5b9f4bd25c2c9f4a964e9269f32225156f44586a8599fac51e
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