Instructions to use hf-internal-testing/tiny-random-MraForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MraForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-MraForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-MraForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-MraForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2fdb4d0c3a63109f7d0cf5d7b28134cfd0ffd068762deb74c8c1aaa9edd1c4e7
- Size of remote file:
- 166 kB
- SHA256:
- 34e62cf912d3a41a8c0b49753091f8c14ef6bc7d3583f98c563908a49df990df
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