Instructions to use hf-internal-testing/tiny-random-TapasForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-TapasForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-TapasForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-TapasForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-TapasForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 87ab0617153a7dec9f722c2e00511d7a04c155485730cf598ccfe8fe0e003225
- Size of remote file:
- 8.63 MB
- SHA256:
- cc106e7645fc62cd61676f3d57bed57fbc4e99ff9c85cff8d4cd6e70818de661
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