Instructions to use hf-tiny-model-private/tiny-random-LukeForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-LukeForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-tiny-model-private/tiny-random-LukeForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-LukeForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-LukeForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c4fc43b2251fb1a819e51df03533f916174a947d5be1f290e1b6a4a34a54d95
- Size of remote file:
- 7 MB
- SHA256:
- 7cf45e35f7d1d4f0d9b7e10b47acf6bf209753042498e0841b387c79985c7519
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