Instructions to use hf-internal-testing/tiny-random-Data2VecTextForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Data2VecTextForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-Data2VecTextForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-Data2VecTextForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 356ab950314f5bd5a9473ba721d4bf513e9612de67dd83914f9cb8cc2e6b81f1
- Size of remote file:
- 377 kB
- SHA256:
- fab9b16818bcc30d23b8682d1ea1e37d5fc8f61d4401b7ba12e3c69fcf169c17
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