Instructions to use hf-tiny-model-private/tiny-random-MegaForMaskedLM 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-MegaForMaskedLM 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-MegaForMaskedLM")# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-MegaForMaskedLM", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6150729eb9328678af7ea3ec2cd76985e1a46566cc2be02888f5216232b78ebd
- Size of remote file:
- 386 kB
- SHA256:
- 51304946a4c73ff744212e963325f65c18f143c98f3deaa2cb8cc0cc10ab12c1
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