Instructions to use hf-tiny-model-private/tiny-random-NystromformerForMaskedLM 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-NystromformerForMaskedLM 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-NystromformerForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-NystromformerForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-NystromformerForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2438c3f4644f9b063dfac1f9738c3771f1dc1161fb1eade4c21b74007e48edd
- Size of remote file:
- 4.19 MB
- SHA256:
- b1e6b0ddac257b2f37f3e602bd0534bb01eaeee158fee64460e1a141607d026c
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