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:
- ab2d286553b90d4fdc0fc89c72ea1fa2c91f0bf98c586fd013e754513aa4946c
- Size of remote file:
- 4.38 MB
- SHA256:
- 02b0cb426fc24ca5691a5bc8b4509e3c9dba06fd56742e66e014f9d210a7dbab
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