Instructions to use hf-internal-testing/tiny-random-IBertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-IBertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-IBertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-IBertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-IBertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a6166fd4fd2946e9b6921a40814f65a3cd4b1c84eb623dd90436231981a86a3
- Size of remote file:
- 734 kB
- SHA256:
- 59d32d50a86978d45c45e58ccb30c20ac6c3a86f44527a5eb12dc406a08d8e68
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