Instructions to use hf-internal-testing/tiny-random-NezhaForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-NezhaForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-NezhaForMaskedLM")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-NezhaForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47f7225d82cede5054f486b06118851bec763ed479ed2acc9c3a0f3909ef1c90
- Size of remote file:
- 2.94 MB
- SHA256:
- 0c2acdd3c48469ab79bc30c88b62cc28f5a09c5c8c87ffb868126733556a4288
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