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:
- 5e37a4ef652c1d682ae207e15151c214130c9c9e367b495bc1aba1ffdfc4f08e
- Size of remote file:
- 410 kB
- SHA256:
- e7fdc6b8e0f849adbd332a7f5ec38ba80d1d4606ca272f4a57ad3f6f3db2b6ad
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