Instructions to use hf-internal-testing/tiny-random-BertForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-BertForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-BertForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-BertForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6e923b82108404c1a413e21e5f8e57afd5781f6b4c601d1e9942c09e658c3f0
- Size of remote file:
- 371 kB
- SHA256:
- 60b5daae9b27cdcc4df0225715ac90e6ebdc38a7a2a5b69c0a1026c885b9808d
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