Instructions to use hf-internal-testing/tiny-random-LukeForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LukeForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-LukeForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LukeForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-LukeForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 360b430c8e54dc42941e02fc209e772866089988fa6c8daa3974ca0f70c80a4d
- Size of remote file:
- 7 MB
- SHA256:
- f0581f07172e2c51520002ea87550f23af9682d3722d5b6f5019c071d2e580c3
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