Instructions to use hf-tiny-model-private/tiny-random-TapasForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-TapasForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-tiny-model-private/tiny-random-TapasForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-TapasForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-TapasForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f1c7fbc850d6dbdd111727046cd9572486f71852012d878d8cd52774f175292
- Size of remote file:
- 4.4 MB
- SHA256:
- 1937a7edb4feb18b8adaeb72eefa79880e064bfc92a61248df8b6f8a79441eeb
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