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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0719bb61557521ce8191e1ee2b52b5b445b7d9ed619c7419617e072930df3ebf
- Size of remote file:
- 185 kB
- SHA256:
- df7ca8d6dd4bc8811bae38c8493ca80b55acd8d56a216636a282d5d967ec214f
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