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:
- 09c3916c3e6b09b62f46934335f227772a6c84ed90d8588484283c3e83e15890
- Size of remote file:
- 823 kB
- SHA256:
- 43f8f57290c1ca492426ee6e2124501618b245599d6cd576dd226c61bae09333
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