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:
- c96b8f3cc6e8ebd76562bda3d7edfbccce67492bb00d56ec48dfbe2d13286ca8
- Size of remote file:
- 371 kB
- SHA256:
- a21060555ded509f3159bbe7aec43a3d58973bb6f6eae3e90f7c93e50e74e58c
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