Instructions to use hf-tiny-model-private/tiny-random-ConvBertForMaskedLM 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-ConvBertForMaskedLM 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-ConvBertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-tiny-model-private/tiny-random-ConvBertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0aeaadf4b82b8a3a07df47c819f3527550aba3becf8e5dc1a069858df14891ed
- Size of remote file:
- 5.45 MB
- SHA256:
- f09659c31ff4859f97e1518373273ae626860b6addcd6713c814634b3286e5d6
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