Instructions to use hf-internal-testing/tiny-random-ConvBertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ConvBertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-ConvBertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-ConvBertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-ConvBertForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7577d7bd57cd922f5ca99c9510304211ea6137cf474ab47e2d3c2e8f1328cc37
- Size of remote file:
- 5.47 MB
- SHA256:
- afd2daf2b27c6a4ef26221e1ee31274eda5111d77b7dc0fc5a62aa6bb34b434a
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