Instructions to use hf-tiny-model-private/tiny-random-BertForMaskedLM 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-BertForMaskedLM 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-BertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-BertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-BertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ce8b678dc5453433e6de01221b8036c48b278b8157cf5d432872dcc69e789c59
- Size of remote file:
- 706 kB
- SHA256:
- b17e56a004c72830c9a034d1d2b94fc217e60cccb5a499cae0ee6c7e27b11a3b
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